allocation_strategies.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bitcoin Allocation Strategies\n",
    "Comparing different allocation strategies historically\n",
    "\n",
    ". Lump-Sum\n",
    "\n",
    ". Dollar Cost Averaging (DCA)\n",
    "\n",
    ". Combination (optimized)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import Libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import urllib\n",
    "import requests\n",
    "import riskfolio as rp\n",
    "from datetime import datetime, timedelta\n",
    "from copy import deepcopy\n",
    "\n",
    "from highcharts import Highchart\n",
    "from chart_builder import plot_chart, CHART_DEFAULTS\n",
    "from IPython.display import display, HTML, display_html\n",
    "import import_ipynb\n",
    "\n",
    "# Chart libraries + settings\n",
    "# plt.style.use('seaborn-whitegrid')\n",
    "pd.options.mode.chained_assignment = None  # default='warn' - disable some pandas warnings\n",
    "pd.options.display.float_format = '{:,.2f}'.format\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load Bitcoin Prices into a dataframe\n",
    "# Ticker is customizable\n",
    "ticker = \"BTC\"\n",
    "# Cryptocompare URL and fiels\n",
    "base_url = 'https://min-api.cryptocompare.com/data/histoday'\n",
    "ticker_field = 'fsym'\n",
    "field_dict = {'tsym': 'USD','allData': 'true'}\n",
    "# Convert the field dict into a url encoded string\n",
    "url_args = \"&\" + urllib.parse.urlencode(field_dict)\n",
    "ticker = ticker.upper()\n",
    "globalURL = (base_url + \"?\" + ticker_field + \"=\" + ticker + url_args)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Success'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Request the data\n",
    "resp = requests.get(url=globalURL)\n",
    "data = resp.json()\n",
    "data[\"Response\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Parse the JSON into a Pandas DataFrame\n",
    "try:\n",
    "    df = pd.DataFrame.from_dict(data['Data'])\n",
    "    df = df.rename(columns={'time': 'date'})\n",
    "    df['date'] = pd.to_datetime(df['date'], unit='s')\n",
    "    df.set_index('date', inplace=True)\n",
    "    df_save = df[['close', 'open', 'high', 'low']]\n",
    "except Exception as e:\n",
    "    print(e)\n",
    "    df_save = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Include percentage change \n",
    "df = df_save\n",
    "df['change'] = df['close'].pct_change()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Support Utilities to be used later"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Increment n number of months of certain date\n",
    "def monthdelta(date, delta):\n",
    "    m, y = (date.month+delta) % 12, date.year + ((date.month)+delta-1) // 12\n",
    "    if not m: m = 12\n",
    "    d = min(date.day, [31,\n",
    "        29 if y%4==0 and not y%400==0 else 28,31,30,31,30,31,31,30,31,30,31][m-1])\n",
    "    new_date = (date.replace(day=d,month=m, year=y))\n",
    "    return new_date\n",
    "\n",
    "def add_periods(date, periods, frequency):\n",
    "    if frequency.upper() == 'D' or 'DAY' in frequency.upper():\n",
    "        return (date + timedelta(days=periods))\n",
    "    if frequency.upper() == 'W' or 'WEEK' in frequency.upper():\n",
    "        return (date + timedelta(days=periods * 7))\n",
    "    if frequency.upper() == 'M' or 'MONTH' in frequency.upper():\n",
    "        return(monthdelta(date, periods))\n",
    "    if frequency.upper() == 'Y' or 'YEAR' in frequency.upper():\n",
    "        return(monthdelta(date, periods * 12))\n",
    "    \n",
    "def annualization_factor(df):\n",
    "    \"\"\"\n",
    "    Receives a df and returns the number of periods to apply\n",
    "    to annualize the returns. For BTC this should be close to\n",
    "    365 as it trades daily. For stocks should be close to 252.\n",
    "    Args:\n",
    "        df (_type_): _description_\n",
    "    \"\"\"\n",
    "    start_date = df.index[0]\n",
    "    end_date = df.index[-1]\n",
    "    number_of_days = (end_date - start_date).days\n",
    "    fraction_of_year = number_of_days / 365\n",
    "    data_points = len(df)\n",
    "    annualization_factor = data_points / fraction_of_year\n",
    "    return int(round(annualization_factor, 0))\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Main Allocation Class\n",
    "See example on creating an allocation instance at the cell following the class definition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "class AllocationManager:\n",
    "    def __init__(self):\n",
    "        self.frequency = 'D'  # 'D', 'W', 'M', 'Y'\n",
    "        self.allocation_periods = 30  # Assume allocation happens during 30 periods\n",
    "        self.upfront_percent = 0  # [0 - 1]: amount to be allocated upfront\n",
    "        self.capital = 100000  # 10,000 dollars to allocate\n",
    "        self.df = df  # Bitcoin Prices Dataframe\n",
    "        self.start_date = self.df.index.min()  # Date where allocation starts (default = first date)\n",
    "                                               # ex: pd.to_datetime('2023-01-01', format='%Y-%m-%d')\n",
    "        self.end_date = self.df.index.max()  # End date for analysis (default = today), but this can be used to test specific timeframes (ex: ending last year)\n",
    "                                             # ex: pd.to_datetime('2023-01-01', format='%Y-%m-%d')\n",
    "        # Create empty allocation & position columns\n",
    "        self.df['allocation'] = 0\n",
    "        self.df['BTC_tx'] = 0\n",
    "        self.risk_free_rate = 0.05\n",
    "         \n",
    "    def allocate_capital(self):\n",
    "        # TRIM THE DF between start and end dates\n",
    "        # Filter the dataframe to only include selected dates\n",
    "        self.df = self.df[(self.df.index >= (self.start_date)) & (self.df.index <= self.end_date)]\n",
    "        \n",
    "        # Clear allocation and other columns\n",
    "        self.df['allocation'] = 0\n",
    "        self.df['BTC_tx'] = 0\n",
    "        self.df['BTC_position'] = 0\n",
    "        self.df['portfolio_position'] = 0\n",
    "        self.df['cum_capital'] = 0\n",
    "        self.df['normalized_port_position'] = 0\n",
    "        self.df['cum_return'] = 0\n",
    "        \n",
    "        # Updates the dataframe to allocate the capital\n",
    "        current_date = self.start_date\n",
    "        periods_left = self.allocation_periods\n",
    "        \n",
    "        # Set upfront amount if any & per period amounts\n",
    "        if self.upfront_percent > 0:\n",
    "            upfront = self.upfront_percent * self.capital  # how much upfront in $\n",
    "            per_period = (self.capital - upfront) / (self.allocation_periods - 1)\n",
    "        else:\n",
    "            per_period = self.capital / self.allocation_periods \n",
    "            upfront = per_period\n",
    "        \n",
    "        # Start looping until allocation is complete\n",
    "        while periods_left > 0:\n",
    "            # Allocate Capital\n",
    "            if current_date == self.start_date:\n",
    "                self.df.at[current_date, 'allocation'] = upfront\n",
    "            else:\n",
    "                self.df.at[current_date, 'allocation'] = per_period\n",
    "            \n",
    "            # Allocate BTC\n",
    "            self.df.at[current_date, 'BTC_tx'] = (\n",
    "                self.df.at[current_date, 'allocation'] / \n",
    "                self.df.at[current_date, 'close'] \n",
    "                )\n",
    "            current_date = add_periods(current_date, 1, self.frequency)\n",
    "            if current_date > self.end_date:\n",
    "                raise Exception(\"Allocation dates overflow end date. Either shorten the allocation period or increase the data range.\")\n",
    "            periods_left -= 1\n",
    "\n",
    "        # Sum all BTC Txs and calculate portfolio values\n",
    "        self.df['BTC_position'] = self.df['BTC_tx'].cumsum()\n",
    "        self.df['portfolio_position'] = (self.df['BTC_position'] * self.df['close'])\n",
    "        self.df = self.df.fillna(0)\n",
    "        # TO DO ---------------------\n",
    "        self.df['cum_capital'] = self.df['allocation'].cumsum()\n",
    "        self.df['normalized_port_position'] = (self.df['portfolio_position'] / \n",
    "                                               self.df['cum_capital']) * 100\n",
    "        self.df['cum_return'] = self.df['normalized_port_position'] / 100\n",
    "\n",
    "    def show_allocations(self):\n",
    "        al_df = self.df.where(self.df.allocation > 0).dropna()\n",
    "        return (al_df)\n",
    "        \n",
    "    def stats(self):\n",
    "        df = deepcopy(self.df)\n",
    "        stats = {}\n",
    "        stats = stats | deepcopy(self.__dict__)\n",
    "        del stats['df'] \n",
    "        stats['capital allocated'] = df.allocation.sum()\n",
    "        stats['BTC allocated'] = df.BTC_tx.sum()\n",
    "        stats['max portfolio value'] = df.portfolio_position.max()\n",
    "        stats['final portfolio value'] = df.portfolio_position[-1]\n",
    "        # Calculate Return on Invested Capital\n",
    "        stats['ROIC'] = (\n",
    "            (stats['final portfolio value'] / \n",
    "             stats['capital allocated']) - 1\n",
    "            )\n",
    "        # Calculate Multiple of Invested Capital\n",
    "        stats['MOIC'] = (\n",
    "            (stats['final portfolio value'] / \n",
    "             stats['capital allocated'])\n",
    "            )\n",
    "        \n",
    "        stats['number_points'] = df['change'].count()\n",
    "        stats['volatility_daily'] = df['change'].std()\n",
    "        stats['annualization_factor'] = annualization_factor(df)\n",
    "        stats['volatility_annual'] = df['change'].std() * annualization_factor(df)**.5\n",
    "        stats['return_annual'] = ((df['cum_return'][-1]) ** (annualization_factor(df) / df['change'].count())) -1\n",
    "    \n",
    "        stats['sharpe_ratio'] = (stats['return_annual'] -\n",
    "                             self.risk_free_rate) / stats['volatility_annual']\n",
    "        Y = df['normalized_port_position'].pct_change().dropna()\n",
    "        stats['hist_VaR_95'] = rp.RiskFunctions.VaR_Hist(Y, alpha=0.05)\n",
    "        stats['max_DD_abs'] = rp.RiskFunctions.MDD_Rel(Y)\n",
    "        stats['avg_DD_abs'] = rp.RiskFunctions.ADD_Rel(Y)\n",
    "        stats['DaR_DD_abs_95'] = rp.RiskFunctions.DaR_Rel(Y, alpha=0.05)\n",
    "        # Bitcoin stats\n",
    "        stats['BTC_initial'] = df['close'][0]\n",
    "        stats['BTC_final'] = df['close'][-1]\n",
    "        stats['BTC_MOIC'] = df['close'][-1] / df['close'][0]\n",
    "        stats['BTC_period'] = (stats['BTC_final'] / stats['BTC_initial']) - 1\n",
    "        \n",
    "        # Compared to BTC - how much more or less $100 invested in the \n",
    "        # allocation strategy resulted compared to $100 in BTC\n",
    "        stats['outperformance_DV100'] = (stats['MOIC'] * 100) - (stats['BTC_MOIC'] * 100)\n",
    "        \n",
    "        #  Cost Basis Statistics\n",
    "        stats['weighted_avg_cost'] =  (stats['capital allocated'] / \n",
    "                                       stats['BTC allocated'])\n",
    "        txs = self.show_allocations()\n",
    "        stats['avg_buy_price'] = txs['close'].mean()\n",
    "        stats['max_buy_price'] = txs['close'].max()\n",
    "        stats['min_buy_price'] = txs['close'].min()\n",
    "        stats['first_buy_price'] = txs['close'][0]\n",
    "        stats['lump_sum_beats_avg'] = (stats['first_buy_price'] < stats['avg_buy_price'])\n",
    "        # Compare the % difference in how many BTC lump sum and DCA represent\n",
    "        stats['BTC_bought_with_dca'] = (self.capital / stats['avg_buy_price'])\n",
    "        stats['BTC_bought_with_ls'] = (self.capital / stats['first_buy_price'])\n",
    "        stats['BTC_bought_ls_over_dca'] =  (stats['BTC_bought_with_ls'] / \n",
    "                                            stats['BTC_bought_with_dca'])\n",
    "        return (stats)\n",
    "    \n",
    "def run_through_time(alloc):\n",
    "    # Do the same allocation for every start date \n",
    "    # in the dataframe. This basically shortens the dataframe by 1 day\n",
    "    # on every loop and stores the results.\n",
    "    # And stores the results in a new df with stats.\n",
    "    \n",
    "    # Stores initial values\n",
    "    stats = {}\n",
    "    stats['inputs'] = stats | deepcopy(alloc.__dict__)\n",
    "    \n",
    "    # Store allocations outputs\n",
    "    stats['outputs'] = {}\n",
    "    # Remove the df to save memory\n",
    "    del stats['inputs']['df'] \n",
    "    tmp_alloc = deepcopy(alloc)  # Creates a copy of Alloc Instance\n",
    "\n",
    "    results = []    \n",
    "    # Will loop from start date until there aren't enough periods to allocate \n",
    "    while True:\n",
    "        try:\n",
    "            tmp_alloc.allocate_capital()\n",
    "            results.append(tmp_alloc.stats())\n",
    "            tmp_alloc.start_date = add_periods(tmp_alloc.start_date, 1, 'D')\n",
    "        except Exception as e:\n",
    "            break\n",
    "    df = pd.DataFrame(results)\n",
    "    \n",
    "    # Create Outputs - sums, averages, depending on column\n",
    "    stats['outputs']['number_of_allocations'] = df['frequency'].count()\n",
    "    stats['outputs']['avg_BTC_allocated'] = df['BTC allocated'].mean()\n",
    "    stats['outputs']['avg_lump_sum_beats_avg'] = df['lump_sum_beats_avg'].mean()\n",
    "    stats['outputs']['avg_ROIC'] = df['ROIC'].mean()\n",
    "    stats['outputs']['avg_sharpe'] = df['sharpe_ratio'].mean()\n",
    "    stats['outputs']['avg_DD'] = df['avg_DD_abs'].mean()\n",
    "    stats['outputs']['avg_DaR_DD_abs_95'] = df['DaR_DD_abs_95'].mean()\n",
    "    stats['outputs']['avg_outperformance_DV100'] = df['outperformance_DV100'].mean()\n",
    "    stats['outputs']['avg_BTC_bought_ls_over_dca'] = df['BTC_bought_ls_over_dca'].mean()\n",
    "    \n",
    "    return (df, stats)\n",
    "        \n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a sample Instance of the AllocationManager and test results\n",
    "btc_alloc = AllocationManager()\n",
    "btc_alloc.capital = 1000000\n",
    "btc_alloc.allocation_periods = 2\n",
    "btc_alloc.frequency = 'D'\n",
    "btc_alloc.start_date = pd.to_datetime('2017-01-01', format='%Y-%m-%d')\n",
    "btc_alloc.upfront_percent = 1\n",
    "btc_alloc.allocate_capital()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>close</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>change</th>\n",
       "      <th>allocation</th>\n",
       "      <th>BTC_tx</th>\n",
       "      <th>BTC_position</th>\n",
       "      <th>portfolio_position</th>\n",
       "      <th>cum_capital</th>\n",
       "      <th>normalized_port_position</th>\n",
       "      <th>cum_return</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-01-01</th>\n",
       "      <td>995.44</td>\n",
       "      <td>963.38</td>\n",
       "      <td>1,001.61</td>\n",
       "      <td>956.10</td>\n",
       "      <td>0.03</td>\n",
       "      <td>1000000</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>1,000,000.00</td>\n",
       "      <td>1000000</td>\n",
       "      <td>100.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-02</th>\n",
       "      <td>1,017.05</td>\n",
       "      <td>995.44</td>\n",
       "      <td>1,031.68</td>\n",
       "      <td>990.20</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>1,021,708.99</td>\n",
       "      <td>1000000</td>\n",
       "      <td>102.17</td>\n",
       "      <td>1.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-03</th>\n",
       "      <td>1,033.30</td>\n",
       "      <td>1,017.05</td>\n",
       "      <td>1,035.47</td>\n",
       "      <td>1,006.53</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>1,038,033.43</td>\n",
       "      <td>1000000</td>\n",
       "      <td>103.80</td>\n",
       "      <td>1.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-04</th>\n",
       "      <td>1,135.41</td>\n",
       "      <td>1,033.30</td>\n",
       "      <td>1,148.54</td>\n",
       "      <td>1,022.32</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>1,140,611.19</td>\n",
       "      <td>1000000</td>\n",
       "      <td>114.06</td>\n",
       "      <td>1.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-05</th>\n",
       "      <td>989.35</td>\n",
       "      <td>1,135.41</td>\n",
       "      <td>1,150.63</td>\n",
       "      <td>874.53</td>\n",
       "      <td>-0.13</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>993,882.10</td>\n",
       "      <td>1000000</td>\n",
       "      <td>99.39</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-27</th>\n",
       "      <td>27,145.09</td>\n",
       "      <td>27,996.81</td>\n",
       "      <td>28,044.15</td>\n",
       "      <td>26,565.75</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>27,269,438.64</td>\n",
       "      <td>1000000</td>\n",
       "      <td>2,726.94</td>\n",
       "      <td>27.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-28</th>\n",
       "      <td>27,274.90</td>\n",
       "      <td>27,145.09</td>\n",
       "      <td>27,501.44</td>\n",
       "      <td>26,660.19</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>27,399,843.29</td>\n",
       "      <td>1000000</td>\n",
       "      <td>2,739.98</td>\n",
       "      <td>27.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-29</th>\n",
       "      <td>28,355.87</td>\n",
       "      <td>27,274.90</td>\n",
       "      <td>28,640.99</td>\n",
       "      <td>27,261.75</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>28,485,765.09</td>\n",
       "      <td>1000000</td>\n",
       "      <td>2,848.58</td>\n",
       "      <td>28.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-30</th>\n",
       "      <td>28,037.46</td>\n",
       "      <td>28,355.87</td>\n",
       "      <td>29,172.90</td>\n",
       "      <td>27,731.64</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>28,165,896.49</td>\n",
       "      <td>1000000</td>\n",
       "      <td>2,816.59</td>\n",
       "      <td>28.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-31</th>\n",
       "      <td>28,473.67</td>\n",
       "      <td>28,037.46</td>\n",
       "      <td>28,557.36</td>\n",
       "      <td>27,541.23</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>28,604,104.72</td>\n",
       "      <td>1000000</td>\n",
       "      <td>2,860.41</td>\n",
       "      <td>28.60</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2281 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               close      open      high       low  change  allocation  \\\n",
       "date                                                                     \n",
       "2017-01-01    995.44    963.38  1,001.61    956.10    0.03     1000000   \n",
       "2017-01-02  1,017.05    995.44  1,031.68    990.20    0.02           0   \n",
       "2017-01-03  1,033.30  1,017.05  1,035.47  1,006.53    0.02           0   \n",
       "2017-01-04  1,135.41  1,033.30  1,148.54  1,022.32    0.10           0   \n",
       "2017-01-05    989.35  1,135.41  1,150.63    874.53   -0.13           0   \n",
       "...              ...       ...       ...       ...     ...         ...   \n",
       "2023-03-27 27,145.09 27,996.81 28,044.15 26,565.75   -0.03           0   \n",
       "2023-03-28 27,274.90 27,145.09 27,501.44 26,660.19    0.00           0   \n",
       "2023-03-29 28,355.87 27,274.90 28,640.99 27,261.75    0.04           0   \n",
       "2023-03-30 28,037.46 28,355.87 29,172.90 27,731.64   -0.01           0   \n",
       "2023-03-31 28,473.67 28,037.46 28,557.36 27,541.23    0.02           0   \n",
       "\n",
       "             BTC_tx  BTC_position  portfolio_position  cum_capital  \\\n",
       "date                                                                 \n",
       "2017-01-01 1,004.58      1,004.58        1,000,000.00      1000000   \n",
       "2017-01-02     0.00      1,004.58        1,021,708.99      1000000   \n",
       "2017-01-03     0.00      1,004.58        1,038,033.43      1000000   \n",
       "2017-01-04     0.00      1,004.58        1,140,611.19      1000000   \n",
       "2017-01-05     0.00      1,004.58          993,882.10      1000000   \n",
       "...             ...           ...                 ...          ...   \n",
       "2023-03-27     0.00      1,004.58       27,269,438.64      1000000   \n",
       "2023-03-28     0.00      1,004.58       27,399,843.29      1000000   \n",
       "2023-03-29     0.00      1,004.58       28,485,765.09      1000000   \n",
       "2023-03-30     0.00      1,004.58       28,165,896.49      1000000   \n",
       "2023-03-31     0.00      1,004.58       28,604,104.72      1000000   \n",
       "\n",
       "            normalized_port_position  cum_return  \n",
       "date                                              \n",
       "2017-01-01                    100.00        1.00  \n",
       "2017-01-02                    102.17        1.02  \n",
       "2017-01-03                    103.80        1.04  \n",
       "2017-01-04                    114.06        1.14  \n",
       "2017-01-05                     99.39        0.99  \n",
       "...                              ...         ...  \n",
       "2023-03-27                  2,726.94       27.27  \n",
       "2023-03-28                  2,739.98       27.40  \n",
       "2023-03-29                  2,848.58       28.49  \n",
       "2023-03-30                  2,816.59       28.17  \n",
       "2023-03-31                  2,860.41       28.60  \n",
       "\n",
       "[2281 rows x 12 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "btc_alloc.df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'frequency': 'D',\n",
       " 'allocation_periods': 30,\n",
       " 'upfront_percent': 0,\n",
       " 'capital': 1000000,\n",
       " 'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       " 'end_date': Timestamp('2023-03-31 00:00:00'),\n",
       " 'risk_free_rate': 0.05,\n",
       " 'capital allocated': 1000000.0,\n",
       " 'BTC allocated': 1107.8983822029695,\n",
       " 'max portfolio value': 74837582.92520191,\n",
       " 'final portfolio value': 31545932.92838123,\n",
       " 'ROIC': 30.54593292838123,\n",
       " 'MOIC': 31.54593292838123,\n",
       " 'number_points': 2281,\n",
       " 'volatility_daily': 0.04085679361198944,\n",
       " 'annualization_factor': 365,\n",
       " 'volatility_annual': 0.7805679459548899,\n",
       " 'return_annual': 0.7372296211488032,\n",
       " 'sharpe_ratio': 0.8804225496450493,\n",
       " 'hist_VaR_95': 0.06305298104296075,\n",
       " 'max_DD_abs': 0.8329062742789147,\n",
       " 'avg_DD_abs': 0.4330476151674484,\n",
       " 'DaR_DD_abs_95': 0.7908566802908588,\n",
       " 'BTC_initial': 995.44,\n",
       " 'BTC_final': 28473.67,\n",
       " 'BTC_MOIC': 28.604104717511852,\n",
       " 'BTC_period': 27.604104717511852,\n",
       " 'outperformance_DV100': 294.182821086938,\n",
       " 'weighted_avg_cost': 902.6098567014585,\n",
       " 'avg_buy_price': 907.8189999999998,\n",
       " 'max_buy_price': 1135.41,\n",
       " 'min_buy_price': 785.43,\n",
       " 'first_buy_price': 995.44,\n",
       " 'lump_sum_beats_avg': False,\n",
       " 'BTC_bought_with_dca': 1101.5411662456945,\n",
       " 'BTC_bought_with_ls': 1004.5808888531704,\n",
       " 'BTC_bought_ls_over_dca': 0.9119776179377962}"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Show statistics\n",
    "btc_alloc.stats()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>close</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>change</th>\n",
       "      <th>allocation</th>\n",
       "      <th>BTC_tx</th>\n",
       "      <th>BTC_position</th>\n",
       "      <th>portfolio_position</th>\n",
       "      <th>cum_capital</th>\n",
       "      <th>normalized_port_position</th>\n",
       "      <th>cum_return</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-01-01</th>\n",
       "      <td>995.44</td>\n",
       "      <td>963.38</td>\n",
       "      <td>1,001.61</td>\n",
       "      <td>956.10</td>\n",
       "      <td>0.03</td>\n",
       "      <td>1000000</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>1,000,000.00</td>\n",
       "      <td>1000000</td>\n",
       "      <td>100.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-02</th>\n",
       "      <td>1,017.05</td>\n",
       "      <td>995.44</td>\n",
       "      <td>1,031.68</td>\n",
       "      <td>990.20</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>1,021,708.99</td>\n",
       "      <td>1000000</td>\n",
       "      <td>102.17</td>\n",
       "      <td>1.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-03</th>\n",
       "      <td>1,033.30</td>\n",
       "      <td>1,017.05</td>\n",
       "      <td>1,035.47</td>\n",
       "      <td>1,006.53</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>1,038,033.43</td>\n",
       "      <td>1000000</td>\n",
       "      <td>103.80</td>\n",
       "      <td>1.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-04</th>\n",
       "      <td>1,135.41</td>\n",
       "      <td>1,033.30</td>\n",
       "      <td>1,148.54</td>\n",
       "      <td>1,022.32</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>1,140,611.19</td>\n",
       "      <td>1000000</td>\n",
       "      <td>114.06</td>\n",
       "      <td>1.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-05</th>\n",
       "      <td>989.35</td>\n",
       "      <td>1,135.41</td>\n",
       "      <td>1,150.63</td>\n",
       "      <td>874.53</td>\n",
       "      <td>-0.13</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>993,882.10</td>\n",
       "      <td>1000000</td>\n",
       "      <td>99.39</td>\n",
       "      <td>0.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-27</th>\n",
       "      <td>27,145.09</td>\n",
       "      <td>27,996.81</td>\n",
       "      <td>28,044.15</td>\n",
       "      <td>26,565.75</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>27,269,438.64</td>\n",
       "      <td>1000000</td>\n",
       "      <td>2,726.94</td>\n",
       "      <td>27.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-28</th>\n",
       "      <td>27,274.90</td>\n",
       "      <td>27,145.09</td>\n",
       "      <td>27,501.44</td>\n",
       "      <td>26,660.19</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>27,399,843.29</td>\n",
       "      <td>1000000</td>\n",
       "      <td>2,739.98</td>\n",
       "      <td>27.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-29</th>\n",
       "      <td>28,355.87</td>\n",
       "      <td>27,274.90</td>\n",
       "      <td>28,640.99</td>\n",
       "      <td>27,261.75</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>28,485,765.09</td>\n",
       "      <td>1000000</td>\n",
       "      <td>2,848.58</td>\n",
       "      <td>28.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-30</th>\n",
       "      <td>28,037.46</td>\n",
       "      <td>28,355.87</td>\n",
       "      <td>29,172.90</td>\n",
       "      <td>27,731.64</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>28,165,896.49</td>\n",
       "      <td>1000000</td>\n",
       "      <td>2,816.59</td>\n",
       "      <td>28.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-03-31</th>\n",
       "      <td>28,473.67</td>\n",
       "      <td>28,037.46</td>\n",
       "      <td>28,557.36</td>\n",
       "      <td>27,541.23</td>\n",
       "      <td>0.02</td>\n",
       "      <td>0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1,004.58</td>\n",
       "      <td>28,604,104.72</td>\n",
       "      <td>1000000</td>\n",
       "      <td>2,860.41</td>\n",
       "      <td>28.60</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2281 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               close      open      high       low  change  allocation  \\\n",
       "date                                                                     \n",
       "2017-01-01    995.44    963.38  1,001.61    956.10    0.03     1000000   \n",
       "2017-01-02  1,017.05    995.44  1,031.68    990.20    0.02           0   \n",
       "2017-01-03  1,033.30  1,017.05  1,035.47  1,006.53    0.02           0   \n",
       "2017-01-04  1,135.41  1,033.30  1,148.54  1,022.32    0.10           0   \n",
       "2017-01-05    989.35  1,135.41  1,150.63    874.53   -0.13           0   \n",
       "...              ...       ...       ...       ...     ...         ...   \n",
       "2023-03-27 27,145.09 27,996.81 28,044.15 26,565.75   -0.03           0   \n",
       "2023-03-28 27,274.90 27,145.09 27,501.44 26,660.19    0.00           0   \n",
       "2023-03-29 28,355.87 27,274.90 28,640.99 27,261.75    0.04           0   \n",
       "2023-03-30 28,037.46 28,355.87 29,172.90 27,731.64   -0.01           0   \n",
       "2023-03-31 28,473.67 28,037.46 28,557.36 27,541.23    0.02           0   \n",
       "\n",
       "             BTC_tx  BTC_position  portfolio_position  cum_capital  \\\n",
       "date                                                                 \n",
       "2017-01-01 1,004.58      1,004.58        1,000,000.00      1000000   \n",
       "2017-01-02     0.00      1,004.58        1,021,708.99      1000000   \n",
       "2017-01-03     0.00      1,004.58        1,038,033.43      1000000   \n",
       "2017-01-04     0.00      1,004.58        1,140,611.19      1000000   \n",
       "2017-01-05     0.00      1,004.58          993,882.10      1000000   \n",
       "...             ...           ...                 ...          ...   \n",
       "2023-03-27     0.00      1,004.58       27,269,438.64      1000000   \n",
       "2023-03-28     0.00      1,004.58       27,399,843.29      1000000   \n",
       "2023-03-29     0.00      1,004.58       28,485,765.09      1000000   \n",
       "2023-03-30     0.00      1,004.58       28,165,896.49      1000000   \n",
       "2023-03-31     0.00      1,004.58       28,604,104.72      1000000   \n",
       "\n",
       "            normalized_port_position  cum_return  \n",
       "date                                              \n",
       "2017-01-01                    100.00        1.00  \n",
       "2017-01-02                    102.17        1.02  \n",
       "2017-01-03                    103.80        1.04  \n",
       "2017-01-04                    114.06        1.14  \n",
       "2017-01-05                     99.39        0.99  \n",
       "...                              ...         ...  \n",
       "2023-03-27                  2,726.94       27.27  \n",
       "2023-03-28                  2,739.98       27.40  \n",
       "2023-03-29                  2,848.58       28.49  \n",
       "2023-03-30                  2,816.59       28.17  \n",
       "2023-03-31                  2,860.41       28.60  \n",
       "\n",
       "[2281 rows x 12 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "btc_alloc.df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'inputs': {'frequency': 'D',\n",
       "  'allocation_periods': 2,\n",
       "  'upfront_percent': 1,\n",
       "  'capital': 1000000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-03-31 00:00:00'),\n",
       "  'risk_free_rate': 0.05},\n",
       " 'outputs': {'number_of_allocations': 2279,\n",
       "  'avg_BTC_allocated': 156.3202809435295,\n",
       "  'avg_lump_sum_beats_avg': 0.0,\n",
       "  'avg_ROIC': 3.4510120938933477,\n",
       "  'avg_sharpe': 1.8630031370035762,\n",
       "  'avg_DD': 0.3590586384019998,\n",
       "  'avg_DaR_DD_abs_95': 0.6641316070185761,\n",
       "  'avg_outperformance_DV100': -4.0842956728641127e-16,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.0}}"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d, stats = run_through_time(btc_alloc)\n",
    "stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 349,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>frequency</th>\n",
       "      <th>allocation_periods</th>\n",
       "      <th>upfront_percent</th>\n",
       "      <th>capital</th>\n",
       "      <th>start_date</th>\n",
       "      <th>end_date</th>\n",
       "      <th>risk_free_rate</th>\n",
       "      <th>capital allocated</th>\n",
       "      <th>BTC allocated</th>\n",
       "      <th>max portfolio value</th>\n",
       "      <th>...</th>\n",
       "      <th>outperformance_DV100</th>\n",
       "      <th>weighted_avg_cost</th>\n",
       "      <th>avg_buy_price</th>\n",
       "      <th>max_buy_price</th>\n",
       "      <th>min_buy_price</th>\n",
       "      <th>first_buy_price</th>\n",
       "      <th>lump_sum_beats_avg</th>\n",
       "      <th>BTC_bought_with_dca</th>\n",
       "      <th>BTC_bought_with_ls</th>\n",
       "      <th>BTC_bought_ls_over_dca</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>W</td>\n",
       "      <td>5</td>\n",
       "      <td>0.50</td>\n",
       "      <td>100000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>100000</td>\n",
       "      <td>106.60</td>\n",
       "      <td>7,200,663.41</td>\n",
       "      <td>...</td>\n",
       "      <td>141.17</td>\n",
       "      <td>938.10</td>\n",
       "      <td>910.17</td>\n",
       "      <td>995.44</td>\n",
       "      <td>821.17</td>\n",
       "      <td>995.44</td>\n",
       "      <td>False</td>\n",
       "      <td>109.87</td>\n",
       "      <td>100.46</td>\n",
       "      <td>0.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>W</td>\n",
       "      <td>5</td>\n",
       "      <td>0.50</td>\n",
       "      <td>100000</td>\n",
       "      <td>2017-01-02</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>100000</td>\n",
       "      <td>105.30</td>\n",
       "      <td>7,113,218.32</td>\n",
       "      <td>...</td>\n",
       "      <td>160.48</td>\n",
       "      <td>949.63</td>\n",
       "      <td>917.27</td>\n",
       "      <td>1,017.05</td>\n",
       "      <td>827.34</td>\n",
       "      <td>1,017.05</td>\n",
       "      <td>False</td>\n",
       "      <td>109.02</td>\n",
       "      <td>98.32</td>\n",
       "      <td>0.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>W</td>\n",
       "      <td>5</td>\n",
       "      <td>0.50</td>\n",
       "      <td>100000</td>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>100000</td>\n",
       "      <td>103.04</td>\n",
       "      <td>6,960,086.39</td>\n",
       "      <td>...</td>\n",
       "      <td>143.91</td>\n",
       "      <td>970.52</td>\n",
       "      <td>939.31</td>\n",
       "      <td>1,033.30</td>\n",
       "      <td>893.75</td>\n",
       "      <td>1,033.30</td>\n",
       "      <td>False</td>\n",
       "      <td>106.46</td>\n",
       "      <td>96.78</td>\n",
       "      <td>0.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>W</td>\n",
       "      <td>5</td>\n",
       "      <td>0.50</td>\n",
       "      <td>100000</td>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>100000</td>\n",
       "      <td>100.99</td>\n",
       "      <td>6,821,478.31</td>\n",
       "      <td>...</td>\n",
       "      <td>296.82</td>\n",
       "      <td>990.24</td>\n",
       "      <td>933.94</td>\n",
       "      <td>1,135.41</td>\n",
       "      <td>785.43</td>\n",
       "      <td>1,135.41</td>\n",
       "      <td>False</td>\n",
       "      <td>107.07</td>\n",
       "      <td>88.07</td>\n",
       "      <td>0.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>W</td>\n",
       "      <td>5</td>\n",
       "      <td>0.50</td>\n",
       "      <td>100000</td>\n",
       "      <td>2017-01-05</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>100000</td>\n",
       "      <td>106.03</td>\n",
       "      <td>7,162,563.42</td>\n",
       "      <td>...</td>\n",
       "      <td>113.99</td>\n",
       "      <td>943.09</td>\n",
       "      <td>922.84</td>\n",
       "      <td>1,003.97</td>\n",
       "      <td>810.11</td>\n",
       "      <td>989.35</td>\n",
       "      <td>False</td>\n",
       "      <td>108.36</td>\n",
       "      <td>101.08</td>\n",
       "      <td>0.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2207</th>\n",
       "      <td>W</td>\n",
       "      <td>5</td>\n",
       "      <td>0.50</td>\n",
       "      <td>100000</td>\n",
       "      <td>2023-01-17</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>100000</td>\n",
       "      <td>4.56</td>\n",
       "      <td>113,227.89</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.97</td>\n",
       "      <td>21,936.37</td>\n",
       "      <td>22,472.99</td>\n",
       "      <td>23,252.78</td>\n",
       "      <td>21,136.12</td>\n",
       "      <td>21,136.12</td>\n",
       "      <td>True</td>\n",
       "      <td>4.45</td>\n",
       "      <td>4.73</td>\n",
       "      <td>1.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2208</th>\n",
       "      <td>W</td>\n",
       "      <td>5</td>\n",
       "      <td>0.50</td>\n",
       "      <td>100000</td>\n",
       "      <td>2023-01-18</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>100000</td>\n",
       "      <td>4.54</td>\n",
       "      <td>112,883.13</td>\n",
       "      <td>...</td>\n",
       "      <td>-6.69</td>\n",
       "      <td>22,003.37</td>\n",
       "      <td>22,953.72</td>\n",
       "      <td>24,332.21</td>\n",
       "      <td>20,678.47</td>\n",
       "      <td>20,678.47</td>\n",
       "      <td>True</td>\n",
       "      <td>4.36</td>\n",
       "      <td>4.84</td>\n",
       "      <td>1.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2209</th>\n",
       "      <td>W</td>\n",
       "      <td>5</td>\n",
       "      <td>0.50</td>\n",
       "      <td>100000</td>\n",
       "      <td>2023-01-19</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>100000</td>\n",
       "      <td>4.55</td>\n",
       "      <td>113,059.48</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.40</td>\n",
       "      <td>21,969.05</td>\n",
       "      <td>22,580.60</td>\n",
       "      <td>23,533.22</td>\n",
       "      <td>21,082.28</td>\n",
       "      <td>21,082.28</td>\n",
       "      <td>True</td>\n",
       "      <td>4.43</td>\n",
       "      <td>4.74</td>\n",
       "      <td>1.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2210</th>\n",
       "      <td>W</td>\n",
       "      <td>5</td>\n",
       "      <td>0.50</td>\n",
       "      <td>100000</td>\n",
       "      <td>2023-01-20</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>100000</td>\n",
       "      <td>4.37</td>\n",
       "      <td>108,450.37</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.00</td>\n",
       "      <td>22,902.73</td>\n",
       "      <td>23,080.86</td>\n",
       "      <td>24,578.28</td>\n",
       "      <td>21,634.86</td>\n",
       "      <td>22,676.20</td>\n",
       "      <td>True</td>\n",
       "      <td>4.33</td>\n",
       "      <td>4.41</td>\n",
       "      <td>1.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2211</th>\n",
       "      <td>W</td>\n",
       "      <td>5</td>\n",
       "      <td>0.50</td>\n",
       "      <td>100000</td>\n",
       "      <td>2023-01-21</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>100000</td>\n",
       "      <td>4.35</td>\n",
       "      <td>108,084.08</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.84</td>\n",
       "      <td>22,980.34</td>\n",
       "      <td>23,130.70</td>\n",
       "      <td>24,638.27</td>\n",
       "      <td>21,862.19</td>\n",
       "      <td>22,789.92</td>\n",
       "      <td>True</td>\n",
       "      <td>4.32</td>\n",
       "      <td>4.39</td>\n",
       "      <td>1.01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2212 rows × 37 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     frequency  allocation_periods  upfront_percent  capital start_date  \\\n",
       "0            W                   5             0.50   100000 2017-01-01   \n",
       "1            W                   5             0.50   100000 2017-01-02   \n",
       "2            W                   5             0.50   100000 2017-01-03   \n",
       "3            W                   5             0.50   100000 2017-01-04   \n",
       "4            W                   5             0.50   100000 2017-01-05   \n",
       "...        ...                 ...              ...      ...        ...   \n",
       "2207         W                   5             0.50   100000 2023-01-17   \n",
       "2208         W                   5             0.50   100000 2023-01-18   \n",
       "2209         W                   5             0.50   100000 2023-01-19   \n",
       "2210         W                   5             0.50   100000 2023-01-20   \n",
       "2211         W                   5             0.50   100000 2023-01-21   \n",
       "\n",
       "       end_date  risk_free_rate  capital allocated  BTC allocated  \\\n",
       "0    2023-02-25            0.05             100000         106.60   \n",
       "1    2023-02-25            0.05             100000         105.30   \n",
       "2    2023-02-25            0.05             100000         103.04   \n",
       "3    2023-02-25            0.05             100000         100.99   \n",
       "4    2023-02-25            0.05             100000         106.03   \n",
       "...         ...             ...                ...            ...   \n",
       "2207 2023-02-25            0.05             100000           4.56   \n",
       "2208 2023-02-25            0.05             100000           4.54   \n",
       "2209 2023-02-25            0.05             100000           4.55   \n",
       "2210 2023-02-25            0.05             100000           4.37   \n",
       "2211 2023-02-25            0.05             100000           4.35   \n",
       "\n",
       "      max portfolio value  ...  outperformance_DV100  weighted_avg_cost  \\\n",
       "0            7,200,663.41  ...                141.17             938.10   \n",
       "1            7,113,218.32  ...                160.48             949.63   \n",
       "2            6,960,086.39  ...                143.91             970.52   \n",
       "3            6,821,478.31  ...                296.82             990.24   \n",
       "4            7,162,563.42  ...                113.99             943.09   \n",
       "...                   ...  ...                   ...                ...   \n",
       "2207           113,227.89  ...                 -3.97          21,936.37   \n",
       "2208           112,883.13  ...                 -6.69          22,003.37   \n",
       "2209           113,059.48  ...                 -4.40          21,969.05   \n",
       "2210           108,450.37  ...                 -1.00          22,902.73   \n",
       "2211           108,084.08  ...                 -0.84          22,980.34   \n",
       "\n",
       "      avg_buy_price  max_buy_price  min_buy_price  first_buy_price  \\\n",
       "0            910.17         995.44         821.17           995.44   \n",
       "1            917.27       1,017.05         827.34         1,017.05   \n",
       "2            939.31       1,033.30         893.75         1,033.30   \n",
       "3            933.94       1,135.41         785.43         1,135.41   \n",
       "4            922.84       1,003.97         810.11           989.35   \n",
       "...             ...            ...            ...              ...   \n",
       "2207      22,472.99      23,252.78      21,136.12        21,136.12   \n",
       "2208      22,953.72      24,332.21      20,678.47        20,678.47   \n",
       "2209      22,580.60      23,533.22      21,082.28        21,082.28   \n",
       "2210      23,080.86      24,578.28      21,634.86        22,676.20   \n",
       "2211      23,130.70      24,638.27      21,862.19        22,789.92   \n",
       "\n",
       "      lump_sum_beats_avg  BTC_bought_with_dca  BTC_bought_with_ls  \\\n",
       "0                  False               109.87              100.46   \n",
       "1                  False               109.02               98.32   \n",
       "2                  False               106.46               96.78   \n",
       "3                  False               107.07               88.07   \n",
       "4                  False               108.36              101.08   \n",
       "...                  ...                  ...                 ...   \n",
       "2207                True                 4.45                4.73   \n",
       "2208                True                 4.36                4.84   \n",
       "2209                True                 4.43                4.74   \n",
       "2210                True                 4.33                4.41   \n",
       "2211                True                 4.32                4.39   \n",
       "\n",
       "      BTC_bought_ls_over_dca  \n",
       "0                       0.91  \n",
       "1                       0.90  \n",
       "2                       0.91  \n",
       "3                       0.82  \n",
       "4                       0.93  \n",
       "...                      ...  \n",
       "2207                    1.06  \n",
       "2208                    1.11  \n",
       "2209                    1.07  \n",
       "2210                    1.02  \n",
       "2211                    1.01  \n",
       "\n",
       "[2212 rows x 37 columns]"
      ]
     },
     "execution_count": 349,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 350,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<h1>Summary Results for DCA</h1>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "        <h3>Inputs</h3>\n",
       "        <table>\n",
       "        <thead>\n",
       "        \n",
       "            <tr>\n",
       "                <td style='text-align: left;'>\n",
       "                frequency\n",
       "                </td>\n",
       "                <td style='text-align: right;'>\n",
       "                W\n",
       "                </td>\n",
       "            </tr>       \n",
       "            \n",
       "            <tr>\n",
       "                <td style='text-align: left;'>\n",
       "                allocation_periods\n",
       "                </td>\n",
       "                <td style='text-align: right;'>\n",
       "                5\n",
       "                </td>\n",
       "            </tr>       \n",
       "            \n",
       "            <tr>\n",
       "                <td style='text-align: left;'>\n",
       "                upfront_percent\n",
       "                </td>\n",
       "                <td style='text-align: right;'>\n",
       "                0.5\n",
       "                </td>\n",
       "            </tr>       \n",
       "            \n",
       "            <tr>\n",
       "                <td style='text-align: left;'>\n",
       "                capital\n",
       "                </td>\n",
       "                <td style='text-align: right;'>\n",
       "                100000\n",
       "                </td>\n",
       "            </tr>       \n",
       "            \n",
       "            <tr>\n",
       "                <td style='text-align: left;'>\n",
       "                start_date\n",
       "                </td>\n",
       "                <td style='text-align: right;'>\n",
       "                2017-01-01 00:00:00\n",
       "                </td>\n",
       "            </tr>       \n",
       "            \n",
       "            <tr>\n",
       "                <td style='text-align: left;'>\n",
       "                end_date\n",
       "                </td>\n",
       "                <td style='text-align: right;'>\n",
       "                2023-02-25 00:00:00\n",
       "                </td>\n",
       "            </tr>       \n",
       "            \n",
       "            <tr>\n",
       "                <td style='text-align: left;'>\n",
       "                risk_free_rate\n",
       "                </td>\n",
       "                <td style='text-align: right;'>\n",
       "                0.05\n",
       "                </td>\n",
       "            </tr>       \n",
       "            \n",
       "        </thead>\n",
       "        </table>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "        <h3>Outputs</h3>\n",
       "        <table>\n",
       "        <thead>\n",
       "        \n",
       "            <tr>\n",
       "                <td style='text-align: left;'>\n",
       "                number_of_allocations\n",
       "                </td>\n",
       "                <td style='text-align: right;'>\n",
       "                2,212.00\n",
       "                </td>\n",
       "            </tr>       \n",
       "            \n",
       "            <tr>\n",
       "                <td style='text-align: left;'>\n",
       "                avg_BTC_allocated\n",
       "                </td>\n",
       "                <td style='text-align: right;'>\n",
       "                15.56\n",
       "                </td>\n",
       "            </tr>       \n",
       "            \n",
       "            <tr>\n",
       "                <td style='text-align: left;'>\n",
       "                avg_lump_sum_beats_avg\n",
       "                </td>\n",
       "                <td style='text-align: right;'>\n",
       "                0.56\n",
       "                </td>\n",
       "            </tr>       \n",
       "            \n",
       "            <tr>\n",
       "                <td style='text-align: left;'>\n",
       "                avg_ROIC\n",
       "                </td>\n",
       "                <td style='text-align: right;'>\n",
       "                2.58\n",
       "                </td>\n",
       "            </tr>       \n",
       "            \n",
       "            <tr>\n",
       "                <td style='text-align: left;'>\n",
       "                avg_sharpe\n",
       "                </td>\n",
       "                <td style='text-align: right;'>\n",
       "                0.35\n",
       "                </td>\n",
       "            </tr>       \n",
       "            \n",
       "            <tr>\n",
       "                <td style='text-align: left;'>\n",
       "                avg_DD\n",
       "                </td>\n",
       "                <td style='text-align: right;'>\n",
       "                0.36\n",
       "                </td>\n",
       "            </tr>       \n",
       "            \n",
       "            <tr>\n",
       "                <td style='text-align: left;'>\n",
       "                avg_DaR_DD_abs_95\n",
       "                </td>\n",
       "                <td style='text-align: right;'>\n",
       "                0.68\n",
       "                </td>\n",
       "            </tr>       \n",
       "            \n",
       "            <tr>\n",
       "                <td style='text-align: left;'>\n",
       "                avg_outperformance_DV100\n",
       "                </td>\n",
       "                <td style='text-align: right;'>\n",
       "                -9.59\n",
       "                </td>\n",
       "            </tr>       \n",
       "            \n",
       "            <tr>\n",
       "                <td style='text-align: left;'>\n",
       "                avg_BTC_bought_ls_over_dca\n",
       "                </td>\n",
       "                <td style='text-align: right;'>\n",
       "                1.03\n",
       "                </td>\n",
       "            </tr>       \n",
       "            \n",
       "        </thead>\n",
       "        </table>\n",
       "        "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<iframe style=\"border:0;outline:none;overflow:hidden\" srcdoc=\"&lt;!DOCTYPE html&gt; &lt;html lang=&quot;en&quot;&gt; &lt;head&gt; &lt;meta charset=&quot;utf-8&quot; /&gt; &lt;link href=&quot;https://www.highcharts.com/highslide/highslide.css&quot; rel=&quot;stylesheet&quot; /&gt; &lt;script type=&quot;text/javascript&quot; src=&quot;https://ajax.googleapis.com/ajax/libs/jquery/1.9.1/jquery.min.js&quot;&gt;&lt;/script&gt; &lt;script type=&quot;text/javascript&quot; src=&quot;https://code.highcharts.com/6/highcharts.js&quot;&gt;&lt;/script&gt; &lt;script type=&quot;text/javascript&quot; src=&quot;https://code.highcharts.com/6/highcharts-more.js&quot;&gt;&lt;/script&gt; &lt;script type=&quot;text/javascript&quot; src=&quot;https://code.highcharts.com/6/modules/heatmap.js&quot;&gt;&lt;/script&gt; &lt;script type=&quot;text/javascript&quot; src=&quot;https://code.highcharts.com/6/modules/exporting.js&quot;&gt;&lt;/script&gt; &lt;/head&gt; &lt;body style=&quot;margin:0;padding:0&quot;&gt; &lt;div id=&quot;container&quot; style=&quot;&quot;&gt;Loading....&lt;/div&gt; &lt;script&gt; $(function(){ Highcharts.setOptions({&quot;global&quot;: {}, &quot;lang&quot;: {}}); var option = {&quot;chart&quot;: {&quot;renderTo&quot;: &quot;container&quot;, &quot;backgroundColor&quot;: &quot;#FFFFFF&quot;, &quot;style&quot;: {&quot;fontFamily&quot;: &quot;Dosis, sans-serif&quot;}}, &quot;colors&quot;: [&quot;#2C6A3E&quot;, &quot;#09654E&quot;, &quot;#005F5A&quot;, &quot;#00585F&quot;, &quot;#1D505F&quot;, &quot;#2F4858&quot;], &quot;credits&quot;: {&quot;enabled&quot;: false}, &quot;drilldown&quot;: {}, &quot;exporting&quot;: {}, &quot;labels&quot;: {}, &quot;legend&quot;: {&quot;itemStyle&quot;: {&quot;fontWeight&quot;: &quot;bold&quot;, &quot;fontSize&quot;: &quot;10px&quot;}}, &quot;loading&quot;: {}, &quot;navigation&quot;: {}, &quot;pane&quot;: {}, &quot;plotOptions&quot;: {}, &quot;series&quot;: {}, &quot;subtitle&quot;: {&quot;text&quot;: &quot;&quot;}, &quot;title&quot;: {&quot;text&quot;: &quot;Outperformance of $100 invested lumpsum compared to cost average&quot;, &quot;style&quot;: {&quot;fontSize&quot;: &quot;12px&quot;, &quot;fontWeight&quot;: &quot;bold&quot;, &quot;textTransform&quot;: &quot;uppercase&quot;}}, &quot;tooltip&quot;: {&quot;borderWidth&quot;: 0, &quot;backgroundColor&quot;: &quot;rgba(219,219,216,0.8)&quot;, &quot;shadow&quot;: false, &quot;valueDecimals&quot;: 2}, &quot;xAxis&quot;: {&quot;gridLineWidth&quot;: 1, &quot;minPadding&quot;: 0, &quot;maxPadding&quot;: 0, &quot;startOnTick&quot;: true, &quot;endOnTick&quot;: true, &quot;labels&quot;: {&quot;style&quot;: {&quot;fontSize&quot;: &quot;10px&quot;}}, &quot;type&quot;: &quot;datetime&quot;, &quot;title&quot;: {&quot;text&quot;: &quot;dates&quot;}}, &quot;yAxis&quot;: {&quot;minorTickInterval&quot;: &quot;auto&quot;, &quot;title&quot;: {&quot;style&quot;: {&quot;textTransform&quot;: &quot;uppercase&quot;}, &quot;text&quot;: &quot;outperformance&quot;}, &quot;labels&quot;: {&quot;style&quot;: {&quot;fontSize&quot;: &quot;10px&quot;}}}}; var chart = new Highcharts.Chart(option); var data = [{&quot;data&quot;: [[1483228800000, 141.16954939356447], [1483315200000, 160.47933310148255], [1483401600000, 143.91124359977493], [1483488000000, 296.81983768506325], [1483574400000, 113.98740358321083], [1483660800000, -30.19941616644155], [1483747200000, -38.8034630408406], [1483833600000, -16.24123904083399], [1483920000000, -25.743187308369215], [1484006400000, -58.63076050321524], [1484092800000, -247.886646223159], [1484179200000, -204.24931349345525], [1484265600000, -186.98344224298853], [1484352000000, -213.6530426101981], [1484438400000, -201.63984601625043], [1484524800000, -196.2256342401638], [1484611200000, -99.71103752696445], [1484697600000, -147.05769043791133], [1484784000000, -111.89839006287184], [1484870400000, -128.7264147321912], [1484956800000, -100.19183322388426], [1485043200000, -91.62601537681167], [1485129600000, -99.49380869517745], [1485216000000, -172.88731621911757], [1485302400000, -178.89388966638944], [1485388800000, -152.01535074636377], [1485475200000, -162.30238655045332], [1485561600000, -164.7708686317028], [1485648000000, -166.42759654131396], [1485734400000, -170.86629152364958], [1485820800000, -133.32969363172833], [1485907200000, -121.22376268392327], [1485993600000, -98.79724735580339], [1486080000000, -104.61338754620874], [1486166400000, -78.51910739334971], [1486252800000, -97.56053082911785], [1486339200000, -99.64752211585437], [1486425600000, -78.6431393334492], [1486512000000, -61.95208366351517], [1486598400000, -180.37299092369813], [1486684800000, -151.86221889740273], [1486771200000, -145.81664382628014], [1486857600000, -173.6033517292435], [1486944000000, -189.2985436216386], [1487030400000, -177.23897746533885], [1487116800000, -168.81048600172426], [1487203200000, -153.567777106618], [1487289600000, -100.68656755367601], [1487376000000, -75.45062831022642], [1487462400000, -108.96925310011147], [1487548800000, -93.55645410433635], [1487635200000, -64.99901460270985], [1487721600000, -35.97916689891963], [1487808000000, 11.907830891544563], [1487894400000, 79.17337762993907], [1487980800000, 63.83959165222768], [1488067200000, 56.934345820365024], [1488153600000, 39.51527421768219], [1488240000000, 29.178495769746178], [1488326400000, 90.5461984934916], [1488412800000, 125.16602192597361], [1488499200000, 202.8611725980984], [1488585600000, 192.33254826111124], [1488672000000, 169.6391569633472], [1488758400000, 131.66311257969505], [1488844800000, 81.78576161842057], [1488931200000, 32.298695515251666], [1489017600000, 76.40769452094537], [1489104000000, 48.29837418920397], [1489190400000, 126.40156541996384], [1489276800000, 139.65251481260339], [1489363200000, 109.49731764386615], [1489449600000, 93.86578760808288], [1489536000000, 125.14962154414206], [1489622400000, 60.5387613437897], [1489708800000, -14.978391820111028], [1489795200000, -133.83676122325733], [1489881600000, -82.97150756498695], [1489968000000, -93.14539488614082], [1490054400000, -24.631516310702864], [1490140800000, -96.6398988220285], [1490227200000, -115.51895970001124], [1490313600000, -241.49363545392362], [1490400000000, -205.8635780366203], [1490486400000, -210.9811099227586], [1490572800000, -140.35925530197392], [1490659200000, -147.93213803996605], [1490745600000, -152.0784138672675], [1490832000000, -173.71301407104056], [1490918400000, -133.64053482971235], [1491004800000, -124.16591991860082], [1491091200000, -122.02492700563175], [1491177600000, -89.64679276292031], [1491264000000, -107.03866165153454], [1491350400000, -127.07710246152033], [1491436800000, -85.51569066503475], [1491523200000, -84.77840133451764], [1491609600000, -96.730832181104], [1491696000000, -82.75955341642702], [1491782400000, -106.04044872361692], [1491868800000, -108.02778455985322], [1491955200000, -130.72764621885153], [1492041600000, -182.15251448557228], [1492128000000, -169.2489416488304], [1492214400000, -181.08707064848568], [1492300800000, -187.16600917869482], [1492387200000, -188.6870184540319], [1492473600000, -191.5550169482733], [1492560000000, -205.58686820347475], [1492646400000, -212.63032276819717], [1492732800000, -196.2464542226146], [1492819200000, -221.5225034555524], [1492905600000, -220.07281277564448], [1492992000000, -241.8652012565217], [1493078400000, -248.50848211191806], [1493164800000, -258.9009377317607], [1493251200000, -237.6266161715082], [1493337600000, -229.03274385775262], [1493424000000, -230.43370859957827], [1493510400000, -231.40700189687823], [1493596800000, -209.66373087875286], [1493683200000, -201.988123779553], [1493769600000, -207.9542841047271], [1493856000000, -203.44966577413516], [1493942400000, -202.19041167211208], [1494028800000, -187.15533793995746], [1494115200000, -191.63866561330724], [1494201600000, -154.7866781161738], [1494288000000, -153.35279882053283], [1494374400000, -147.3881348175887], [1494460800000, -132.7091697367714], [1494547200000, -189.63216505851233], [1494633600000, -158.8723004468361], [1494720000000, -166.12910951082813], [1494806400000, -196.81597829484258], [1494892800000, -201.13295256699075], [1494979200000, -172.6084537604911], [1495065600000, -147.1034453285506], [1495152000000, -125.79735486466802], [1495238400000, -103.18845554782172], [1495324800000, -107.3788884583571], [1495411200000, -90.72041237048973], [1495497600000, -64.36790304228452], [1495584000000, -14.753461412209958], [1495670400000, -53.22498680189335], [1495756800000, -73.9551628222656], [1495843200000, -128.88773507740655], [1495929600000, -88.38786459221137], [1496016000000, -62.848640000671026], [1496102400000, -102.67333128279665], [1496188800000, -57.000951906521095], [1496275200000, -38.23859174016127], [1496361600000, -22.51386687256479], [1496448000000, -14.793802118455119], [1496534400000, -19.244369534975363], [1496620800000, 22.221247635127042], [1496707200000, 30.826293991724015], [1496793600000, 17.55542259097524], [1496880000000, 34.73804565961234], [1496966400000, 41.87975797660408], [1497052800000, 53.40794295298099], [1497139200000, 67.35997831403404], [1497225600000, 28.944874060470966], [1497312000000, 25.291550130796168], [1497398400000, -18.147830407843912], [1497484800000, -21.191101274785865], [1497571200000, 6.5912742003873745], [1497657600000, 54.07801186155143], [1497744000000, 38.289278778841435], [1497830400000, 41.19254468139479], [1497916800000, 51.179570619729475], [1498003200000, 37.02405827805444], [1498089600000, 21.996512093726892], [1498176000000, 42.10365063843756], [1498262400000, 33.56436354256073], [1498348800000, 29.838365485390227], [1498435200000, -2.9656406539436375], [1498521600000, 23.670733066146], [1498608000000, 21.197989200216625], [1498694400000, -10.712909459455659], [1498780800000, -10.637216436597896], [1498867200000, -10.109789330176227], [1498953600000, 19.4982942028837], [1499040000000, 8.086420117428474], [1499126400000, 24.19406326790613], [1499212800000, 25.977768863906817], [1499299200000, -8.76837216221827], [1499385600000, -18.9839653106568], [1499472000000, -8.152598170529359], [1499558400000, -10.528940533242576], [1499644800000, -73.58388641857312], [1499731200000, -71.01276888355392], [1499817600000, -48.703600803759514], [1499904000000, -93.38454503997241], [1499990400000, -126.2141933106177], [1500076800000, -213.24524676961698], [1500163200000, -232.75615703406334], [1500249600000, -160.143044667906], [1500336000000, -126.67848987254752], [1500422400000, -134.35252858742092], [1500508800000, -41.00204232885028], [1500595200000, -78.84165173278802], [1500681600000, -68.57253583143108], [1500768000000, -82.7976108619822], [1500854400000, -93.66845588958756], [1500940800000, -117.3578943251872], [1501027200000, -122.81291120566482], [1501113600000, -107.15349907165057], [1501200000000, -95.2244227422292], [1501286400000, -122.94660039877203], [1501372800000, -119.05574666150744], [1501459200000, -110.5899350826121], [1501545600000, -132.82268166882477], [1501632000000, -139.10566789275015], [1501718400000, -130.782254431174], [1501804800000, -126.46340831419593], [1501891200000, -79.97601529450526], [1501977600000, -85.82473392640554], [1502064000000, -66.94484160383684], [1502150400000, -68.17982450450302], [1502236800000, -83.43379407564635], [1502323200000, -79.1592471153042], [1502409600000, -53.896748729790374], [1502496000000, -32.5141151446735], [1502582400000, -16.17010406522263], [1502668800000, 7.082141166664655], [1502755200000, -9.157575236929915], [1502841600000, 6.570940626970469], [1502928000000, 9.199418788525804], [1503014400000, -11.96183058790325], [1503100800000, -4.117287642872384], [1503187200000, -8.671695294385813], [1503273600000, -15.991486261329896], [1503360000000, -10.749737148837085], [1503446400000, -4.383593811964602], [1503532800000, 24.54939033403116], [1503619200000, 18.618173132437278], [1503705600000, 18.562066426217143], [1503792000000, 21.71289461114543], [1503878400000, 16.80336103023228], [1503964800000, 31.597155341293956], [1504051200000, 27.901623792037867], [1504137600000, 55.7796846002239], [1504224000000, 58.92722177153803], [1504310400000, 34.423338830061084], [1504396800000, 40.00064131371056], [1504483200000, 7.217634423783011], [1504569600000, 22.35691761931912], [1504656000000, 35.739556351837734], [1504742400000, 55.07526915133269], [1504828800000, 26.096956678653896], [1504915200000, 19.08302621231155], [1505001600000, 13.092298812729837], [1505088000000, -3.9265159281704882], [1505174400000, -2.0918259355748887], [1505260800000, -27.066341652964297], [1505347200000, -87.10568013001057], [1505433600000, -44.13598856290014], [1505520000000, -54.87451936788284], [1505606400000, -55.08807216881985], [1505692800000, -31.932134025997016], [1505779200000, -42.04489888466355], [1505865600000, -48.642177707266], [1505952000000, -79.4568299154131], [1506038400000, -85.69825063840153], [1506124800000, -75.58508577067369], [1506211200000, -87.28659361139921], [1506297600000, -68.25961155223968], [1506384000000, -64.89482044534486], [1506470400000, -43.54889704444321], [1506556800000, -55.33468664544182], [1506643200000, -60.95953391191699], [1506729600000, -51.45891395542378], [1506816000000, -53.448164530728036], [1506902400000, -55.517800037531515], [1506988800000, -58.11181451412568], [1507075200000, -68.59836456939342], [1507161600000, -72.95005751870451], [1507248000000, -73.96173266104273], [1507334400000, -72.74929607782224], [1507420800000, -65.06316526268381], [1507507200000, -53.81155671032349], [1507593600000, -52.85705137033983], [1507680000000, -55.363441605738444], [1507766400000, -31.13585909634122], [1507852800000, -22.158159238248913], [1507939200000, -14.969229460646261], [1508025600000, -19.528347891784847], [1508112000000, -18.633029161705963], [1508198400000, -24.626126708992217], [1508284800000, -35.32658040273367], [1508371200000, -35.09537691728019], [1508457600000, -20.679931558968974], [1508544000000, -19.900783930687282], [1508630400000, -21.874885810581873], [1508716800000, -27.576812818027292], [1508803200000, -44.45680149435276], [1508889600000, -44.858331569736606], [1508976000000, -41.56947242094594], [1509062400000, -43.09297571927863], [1509148800000, -46.61484381799971], [1509235200000, -32.63513266986695], [1509321600000, -37.95907358540808], [1509408000000, -29.671866882210168], [1509494400000, -28.43364200536797], [1509580800000, -21.9815796804225], [1509667200000, -18.129958332449462], [1509753600000, -14.679875012980744], [1509840000000, -14.543956029150365], [1509926400000, -32.0115075747982], [1510012800000, -29.156336174432965], [1510099200000, -29.9430025987121], [1510185600000, -42.828406555030085], [1510272000000, -58.34093157710225], [1510358400000, -65.8566993601114], [1510444800000, -84.34446585808604], [1510531200000, -69.95530422193332], [1510617600000, -68.29949691142969], [1510704000000, -55.170507720187175], [1510790400000, -47.1037401398016], [1510876800000, -53.5520459750266], [1510963200000, -54.355977690022485], [1511049600000, -52.37503406221933], [1511136000000, -52.85052715770877], [1511222400000, -55.049328489673115], [1511308800000, -54.37854999849145], [1511395200000, -61.663646283755895], [1511481600000, -58.446617440709076], [1511568000000, -50.787613838237746], [1511654400000, -42.80766196914615], [1511740800000, -40.28042814964357], [1511827200000, -39.94798225816149], [1511913600000, -42.19951355634598], [1512000000000, -42.715792793043704], [1512086400000, -30.602968781254106], [1512172800000, -28.225204649867777], [1512259200000, -26.467473351187834], [1512345600000, -24.419770419448582], [1512432000000, -27.58654959362508], [1512518400000, -10.899563853569987], [1512604800000, 6.505012343624458], [1512691200000, 2.639329320673795], [1512777600000, -2.9582028690279287], [1512864000000, -1.9607072370071421], [1512950400000, 7.784876831755383], [1513036800000, 6.6914379276535385], [1513123200000, 3.740814286441207], [1513209600000, 9.064235324672893], [1513296000000, 13.413532481887955], [1513382400000, 20.38427054226159], [1513468800000, 20.07447838212161], [1513555200000, 21.82850415038378], [1513641600000, 17.45122769397014], [1513728000000, 12.7785847619258], [1513814400000, 12.66303848775155], [1513900800000, -1.4994823688647045], [1513987200000, 2.476609189767231], [1514073600000, 1.0508181860292325], [1514160000000, 5.121423026885424], [1514246400000, 18.321982298076506], [1514332800000, 14.547561275052402], [1514419200000, 12.119445810781656], [1514505600000, 8.665526819213937], [1514592000000, -7.260740387012163], [1514678400000, 5.086497435485882], [1514764800000, 6.9261739143859415], [1514851200000, 22.32005834806813], [1514937600000, 22.40764878649611], [1515024000000, 28.82552716611417], [1515110400000, 36.17971740329864], [1515196800000, 31.855185092152993], [1515283200000, 34.50560945524603], [1515369600000, 37.90360166192107], [1515456000000, 38.23440190536567], [1515542400000, 39.78834207122435], [1515628800000, 31.367604383153235], [1515715200000, 33.20999196772647], [1515801600000, 31.447815842142973], [1515888000000, 35.53182569697492], [1515974400000, 41.50245494546974], [1516060800000, 23.96119207093517], [1516147200000, 18.41104265842955], [1516233600000, 17.811951575202187], [1516320000000, 19.755427381229197], [1516406400000, 25.65302161360728], [1516492800000, 22.996142090582083], [1516579200000, 18.661231522579413], [1516665600000, 19.044344301775652], [1516752000000, 23.082981016346878], [1516838400000, 21.28227741694684], [1516924800000, 18.36583630021792], [1517011200000, 19.794700913442], [1517097600000, 30.32068522893337], [1517184000000, 24.877370005277697], [1517270400000, 9.870825143310043], [1517356800000, 10.968317646928796], [1517443200000, -7.210203616208787], [1517529600000, -14.067761194558614], [1517616000000, -10.147645451815862], [1517702400000, -21.85849729187231], [1517788800000, -54.80570898712267], [1517875200000, -36.20466406271834], [1517961600000, -36.92854666828515], [1518048000000, -24.19082015193274], [1518134400000, -18.64530588152482], [1518220800000, -20.90473207762693], [1518307200000, -29.604825927926555], [1518393600000, -18.912265656936654], [1518480000000, -23.731428643314985], [1518566400000, -2.044102746565443], [1518652800000, 6.512164628912984], [1518739200000, 7.195593607814345], [1518825600000, 20.207093397945556], [1518912000000, 9.624318421227628], [1518998400000, 14.910216867037548], [1519084800000, 15.35959075664988], [1519171200000, 14.301728724708028], [1519257600000, 8.106614379041588], [1519344000000, 10.970551841994421], [1519430400000, 9.367012074611779], [1519516800000, 4.370809607926219], [1519603200000, 13.813628795389747], [1519689600000, 18.660475501904244], [1519776000000, 21.034970746843868], [1519862400000, 33.798429804189766], [1519948800000, 35.751137489140206], [1520035200000, 43.86324590960993], [1520121600000, 41.12428308035231], [1520208000000, 40.1555020571206], [1520294400000, 31.968139937267722], [1520380800000, 29.70806217238001], [1520467200000, 27.069158774365746], [1520553600000, 27.86490913972625], [1520640000000, 22.335975465258628], [1520726400000, 31.266344789207352], [1520812800000, 25.78646249534799], [1520899200000, 24.00560010137758], [1520985600000, 11.82302622115202], [1521072000000, 12.920706926112757], [1521158400000, 15.011515136488867], [1521244800000, 6.558687698935273], [1521331200000, 11.105136572622484], [1521417600000, 20.46012083174344], [1521504000000, 24.700621176987568], [1521590400000, 25.55097860309769], [1521676800000, 21.874045199991656], [1521763200000, 25.340215134597088], [1521849600000, 16.43651418900447], [1521936000000, 14.008929660490708], [1522022400000, 9.552304944744094], [1522108800000, -0.6932641388373213], [1522195200000, 6.413189092996561], [1522281600000, -17.60388726479664], [1522368000000, -23.50028233860735], [1522454400000, -25.285949089198255], [1522540800000, -29.968295088746856], [1522627200000, -21.471747820674295], [1522713600000, -15.098472546780272], [1522800000000, -28.868489843243992], [1522886400000, -37.96517670551253], [1522972800000, -42.71810409872734], [1523059200000, -38.27885251141049], [1523145600000, -35.82904877785808], [1523232000000, -39.97492962359979], [1523318400000, -38.34607298439272], [1523404800000, -35.31877932979444], [1523491200000, -18.114431637823714], [1523577600000, -17.245282391412957], [1523664000000, -17.343496463468227], [1523750400000, -11.314854387996832], [1523836800000, -15.37274226778186], [1523923200000, -18.54984971341321], [1524009600000, -11.573257068423288], [1524096000000, -10.591281983018632], [1524182400000, 1.2551461384418872], [1524268800000, -0.02479541440760613], [1524355200000, -3.260783398937008], [1524441600000, 0.8087752335042637], [1524528000000, 13.701935558721033], [1524614400000, 5.1412558947928915], [1524700800000, 10.959460367484894], [1524787200000, 8.43672399362356], [1524873600000, 14.03489091335021], [1524960000000, 13.306548368075823], [1525046400000, 13.986604435045422], [1525132800000, 12.902505072278302], [1525219200000, 17.915468748364077], [1525305600000, 25.657805724385668], [1525392000000, 27.06098687449432], [1525478400000, 28.618073635532653], [1525564800000, 23.75026867925297], [1525651200000, 23.356788483890284], [1525737600000, 20.955926460897018], [1525824000000, 25.78065652308848], [1525910400000, 21.85308631205021], [1525996800000, 12.617773107236417], [1526083200000, 14.305155318829406], [1526169600000, 20.378693038528695], [1526256000000, 21.98426853245587], [1526342400000, 20.34219096389785], [1526428800000, 22.453597907612163], [1526515200000, 14.349739489140802], [1526601600000, 19.83600635377229], [1526688000000, 19.760324230967456], [1526774400000, 28.471407955541963], [1526860800000, 26.66310427397741], [1526947200000, 18.750814093639974], [1527033600000, 11.272031255309628], [1527120000000, 10.089934370852461], [1527206400000, 14.478569107495048], [1527292800000, 10.35059682318672], [1527379200000, 14.684590053203692], [1527465600000, 7.253945764304035], [1527552000000, 17.538695378443947], [1527638400000, 16.856738364501723], [1527724800000, 19.061220580061956], [1527811200000, 23.766233570811323], [1527897600000, 23.649580482853196], [1527984000000, 30.02295350178082], [1528070400000, 20.662236248677402], [1528156800000, 27.13512195678402], [1528243200000, 28.410196146596206], [1528329600000, 29.654954019689228], [1528416000000, 31.558692736085277], [1528502400000, 25.332338242736284], [1528588800000, 9.647471008290267], [1528675200000, 8.331765941745516], [1528761600000, 4.230986301560279], [1528848000000, -4.3143328950592945], [1528934400000, 8.602537227797427], [1529020800000, 3.766135411375899], [1529107200000, 3.211083377201703], [1529193600000, 1.9994039447551586], [1529280000000, 3.8798336794295665], [1529366400000, 5.618603001985207], [1529452800000, 4.250231188287955], [1529539200000, 6.266818316702086], [1529625600000, -14.789122524864183], [1529712000000, -14.23154038946592], [1529798400000, -14.498798007413598], [1529884800000, -17.216069222843032], [1529971200000, -25.6372747512018], [1530057600000, -24.521281297110647], [1530144000000, -31.214498427783553], [1530230400000, -21.327995534501554], [1530316800000, -17.93357937695606], [1530403200000, -19.520708208840915], [1530489600000, -15.64486644581251], [1530576000000, -20.416840413145337], [1530662400000, -17.63288509222616], [1530748800000, -17.210277619207318], [1530835200000, -14.938079670174204], [1530921600000, -9.580356712271396], [1531008000000, -11.601053354138799], [1531094400000, -15.97742068895269], [1531180800000, -28.914456325576452], [1531267200000, -22.18921923480508], [1531353600000, -27.15391084132932], [1531440000000, -24.766768559874833], [1531526400000, -22.66438890134316], [1531612800000, -20.54497477455635], [1531699200000, -10.894594458841595], [1531785600000, 3.5848646808419176], [1531872000000, 8.770323392959199], [1531958400000, 9.941763229635683], [1532044800000, 7.425496555433995], [1532131200000, 11.53529730081624], [1532217600000, 10.060140738335122], [1532304000000, 19.30097704559398], [1532390400000, 33.60556543352112], [1532476800000, 33.73038907469288], [1532563200000, 26.587593705158895], [1532649600000, 31.40092676047152], [1532736000000, 34.764019024421316], [1532822400000, 33.314804167461205], [1532908800000, 34.04982429494203], [1532995200000, 25.288365798225243], [1533081600000, 26.38361051752571], [1533168000000, 21.964290130990435], [1533254400000, 19.062108950248557], [1533340800000, 9.571959311155354], [1533427200000, 8.540118376617556], [1533513600000, 7.3030339295825115], [1533600000000, -0.8311160302766893], [1533686400000, -8.340548024582574], [1533772800000, -1.1181655659961507], [1533859200000, -14.655729583378331], [1533945600000, -10.456433249121005], [1534032000000, -9.494889604991727], [1534118400000, -11.17641062388958], [1534204800000, -15.977025935622692], [1534291200000, -9.10987793518359], [1534377600000, -8.390928888265648], [1534464000000, -1.542856628356958], [1534550400000, -6.566577481553679], [1534636800000, -4.4848692503414895], [1534723200000, -10.918667603134622], [1534809600000, -6.6414870173176155], [1534896000000, -6.69541530899528], [1534982400000, -2.1874210380913155], [1535068800000, 1.182860680603028], [1535155200000, 2.7837361101601346], [1535241600000, 1.374600203852765], [1535328000000, 8.298064377931041], [1535414400000, 12.462206154946273], [1535500800000, 14.581557063043704], [1535587200000, 11.281156122452387], [1535673600000, 11.349538347694136], [1535760000000, 17.137197578610028], [1535846400000, 19.00252335328429], [1535932800000, 20.444440091512035], [1536019200000, 23.632406037810085], [1536105600000, 7.551508651819461], [1536192000000, -1.333904671930327], [1536278400000, -5.838642327801381], [1536364800000, -11.425109663408307], [1536451200000, -9.957493690629462], [1536537600000, -5.420288046210146], [1536624000000, -5.296974393540097], [1536710400000, -4.082296727086714], [1536796800000, 0.04365420579523516], [1536883200000, -2.1202059396960635], [1536969600000, -0.4832693425138359], [1537056000000, -1.208431355094433], [1537142400000, -9.682768338899791], [1537228800000, -5.460066738179762], [1537315200000, -3.5338998749851953], [1537401600000, 0.5388807468215191], [1537488000000, 7.037671167548524], [1537574400000, 6.110753750546394], [1537660800000, 5.342954845056852], [1537747200000, -0.027560039719560336], [1537833600000, -3.115559723776812], [1537920000000, -1.8542430181792042], [1538006400000, 6.786715788708591], [1538092800000, 4.98736385827408], [1538179200000, 4.084664359376063], [1538265600000, 4.3234881012475626], [1538352000000, 2.2152362963535666], [1538438400000, 0.7950292443746321], [1538524800000, 0.0026464784960467114], [1538611200000, 5.366758726566275], [1538697600000, 6.5356750696715835], [1538784000000, 5.180789945974595], [1538870400000, 4.633090381565296], [1538956800000, 5.112033748448766], [1539043200000, 4.635897801863052], [1539129600000, 2.7355121529632243], [1539216000000, -6.750064254966446], [1539302400000, -4.971591072994556], [1539388800000, -4.72480480083351], [1539475200000, -5.269518476620249], [1539561600000, 5.743802138541412], [1539648000000, 5.031996350996508], [1539734400000, 8.903265943543943], [1539820800000, 7.813000298310953], [1539907200000, 8.258382745899667], [1539993600000, 8.911638785065804], [1540080000000, 8.292322010829594], [1540166400000, 17.704823268655446], [1540252800000, 22.268778105314993], [1540339200000, 24.443230936293162], [1540425600000, 29.145836313410484], [1540512000000, 29.5839002260588], [1540598400000, 38.49983518322591], [1540684800000, 34.58095140880363], [1540771200000, 43.36705627785716], [1540857600000, 47.35170883351617], [1540944000000, 42.796526444420635], [1541030400000, 48.878966269580985], [1541116800000, 54.571919011251225], [1541203200000, 59.27874224366519], [1541289600000, 59.391065828069486], [1541376000000, 76.31938450735998], [1541462400000, 80.57915839569978], [1541548800000, 80.86516327113048], [1541635200000, 88.56137423723328], [1541721600000, 93.05652077698954], [1541808000000, 97.94463794649312], [1541894400000, 92.89682319615457], [1541980800000, 112.48043895188897], [1542067200000, 115.80753009851941], [1542153600000, 89.09106808310241], [1542240000000, 99.40874085248271], [1542326400000, 104.88952554870292], [1542412800000, 108.54099627292226], [1542499200000, 104.66599130275375], [1542585600000, 75.03567450278064], [1542672000000, 50.99285559056932], [1542758400000, 53.37493388656986], [1542844800000, 39.84919250063206], [1542931200000, 53.55650515547484], [1543017600000, 13.18275953774446], [1543104000000, 22.24091002691671], [1543190400000, 4.776334877084423], [1543276800000, 8.87497527140988], [1543363200000, 41.298310044218965], [1543449600000, 49.51755243553862], [1543536000000, 32.65098271885461], [1543622400000, 44.79755330228761], [1543708800000, 36.326934976512916], [1543795200000, 14.043957942388374], [1543881600000, 19.70859538218474], [1543968000000, -0.9825756200842761], [1544054400000, -19.686579472295534], [1544140800000, -26.55352156897527], [1544227200000, -21.957713192735696], [1544313600000, -16.15649242984034], [1544400000000, -32.50774264774816], [1544486400000, -40.52489898283818], [1544572800000, -34.671778606231555], [1544659200000, -46.26019031227759], [1544745600000, -56.275439397243986], [1544832000000, -55.91679687654391], [1544918400000, -56.676098307665825], [1545004800000, -28.341461694258214], [1545091200000, -9.869617299552942], [1545177600000, -10.570912339605115], [1545264000000, 32.241610636017526], [1545350400000, 9.233693893227269], [1545436800000, 21.53246651893187], [1545523200000, 18.44234956125422], [1545609600000, 24.07067486042274], [1545696000000, 4.560846290127188], [1545782400000, 4.184264665153933], [1545868800000, -4.16974900408286], [1545955200000, 20.31124776096385], [1546041600000, 7.180663241065531], [1546128000000, 17.090713070075594], [1546214400000, 5.458341805485361], [1546300800000, 18.07698167049091], [1546387200000, 22.978280831133475], [1546473600000, 20.1901778579263], [1546560000000, 23.602304544783124], [1546646400000, 19.12575470288516], [1546732800000, 45.211920862854754], [1546819200000, 41.206881046532885], [1546905600000, 42.08466355348389], [1546992000000, 42.900838565849995], [1547078400000, 13.285877026945286], [1547164800000, 7.232991424670672], [1547251200000, 3.8451957884979038], [1547337600000, -1.244592999259794], [1547424000000, 16.64735130081931], [1547510400000, 9.214618943808773], [1547596800000, 12.228797323830008], [1547683200000, 16.842580861144484], [1547769600000, 6.612767176784928], [1547856000000, 11.742438056917877], [1547942400000, -2.0126881572288084], [1548028800000, -1.8235995004657752], [1548115200000, 0.972601403337535], [1548201600000, -2.2616409418428702], [1548288000000, 2.4548044474532844], [1548374400000, -7.183851965915096], [1548460800000, -10.319461166091514], [1548547200000, -6.666174675271918], [1548633600000, -21.34988751259766], [1548720000000, -24.984454225455806], [1548806400000, -19.8563877124584], [1548892800000, -21.35449744824939], [1548979200000, -26.435030765740635], [1549065600000, -25.442483248391795], [1549152000000, -25.382604428591094], [1549238400000, -30.235772718363137], [1549324800000, -31.292131307943464], [1549411200000, -37.40561507415998], [1549497600000, -38.30862663747473], [1549584000000, -12.657228048409706], [1549670400000, -18.452742433823573], [1549756800000, -8.9425409222398], [1549843200000, -18.941519443188554], [1549929600000, -21.18661915939697], [1550016000000, -23.195926770424308], [1550102400000, -24.09833254457078], [1550188800000, -25.265329675736893], [1550275200000, -29.583299762108254], [1550361600000, -16.554951021673446], [1550448000000, 4.158904664957618], [1550534400000, 1.8400220196249393], [1550620800000, 4.862668387112308], [1550707200000, 3.145073216826745], [1550793600000, 5.741754748206745], [1550880000000, 13.601739877384148], [1550966400000, -12.438958377918198], [1551052800000, -2.4691763707432983], [1551139200000, -8.69386927686412], [1551225600000, -9.95040684838716], [1551312000000, -9.502397842644541], [1551398400000, -10.815022134687752], [1551484800000, -13.465165342863997], [1551571200000, -14.691480011242675], [1551657600000, -19.412299697997355], [1551744000000, -19.929753562055453], [1551830400000, -22.938581744463704], [1551916800000, -20.44199529075729], [1552003200000, -25.33805115928851], [1552089600000, -21.494504780138072], [1552176000000, -23.54762308443867], [1552262400000, -27.875375791975898], [1552348800000, -37.48270597040687], [1552435200000, -42.736325754388304], [1552521600000, -37.64639776384922], [1552608000000, -37.49265814579417], [1552694400000, -30.56162795006685], [1552780800000, -34.80736661217827], [1552867200000, -34.39456749705221], [1552953600000, -43.80766970179843], [1553040000000, -45.66601910438294], [1553126400000, -46.66084334744505], [1553212800000, -49.65675162897651], [1553299200000, -49.73033835032072], [1553385600000, -52.87308961172528], [1553472000000, -59.0695674190257], [1553558400000, -70.75768910829345], [1553644800000, -64.76147683606723], [1553731200000, -59.375340779022395], [1553817600000, -56.92449682844091], [1553904000000, -56.8335747799415], [1553990400000, -59.944865106209534], [1554076800000, -57.430762029791424], [1554163200000, -18.290628114556398], [1554249600000, -16.060838061500135], [1554336000000, -14.797045500306524], [1554422400000, -12.074013380431438], [1554508800000, -12.618805115817736], [1554595200000, -7.109867969382492], [1554681600000, -1.9507962204364162], [1554768000000, -10.902750710284238], [1554854400000, -7.334093410505091], [1554940800000, -18.89234931633257], [1555027200000, -21.89382148818936], [1555113600000, -28.17205370068865], [1555200000000, -23.078246829840907], [1555286400000, -33.25604695231891], [1555372800000, -29.531081568446382], [1555459200000, -30.498225745093976], [1555545600000, -26.340898542419836], [1555632000000, -28.035928242780926], [1555718400000, -32.14739790682415], [1555804800000, -36.287420029232464], [1555891200000, -35.47823058824821], [1555977600000, -32.26511996231818], [1556064000000, -36.71721133808899], [1556150400000, -50.86755968193319], [1556236800000, -49.54928087807781], [1556323200000, -55.431539739186974], [1556409600000, -59.226835347694646], [1556496000000, -64.00423415882307], [1556582400000, -60.321389096946916], [1556668800000, -59.413344513342395], [1556755200000, -54.70420277761605], [1556841600000, -46.06755834962348], [1556928000000, -48.06921854823389], [1557014400000, -56.306227404277195], [1557100800000, -59.104647034201776], [1557187200000, -54.960590606571145], [1557273600000, -48.7769303121828], [1557360000000, -41.730951146633345], [1557446400000, -36.346908362704994], [1557532800000, -14.825526269959823], [1557619200000, -26.246062666801606], [1557705600000, -7.367537600312005], [1557792000000, -1.1998449675098755], [1557878400000, 2.426604944436747], [1557964800000, -3.074040330549394], [1558051200000, -17.416605255324953], [1558137600000, -20.273008272668676], [1558224000000, -4.877228776363211], [1558310400000, -8.982147627974996], [1558396800000, -6.2970984984094684], [1558483200000, -14.543181276005896], [1558569600000, -9.38140754083372], [1558656000000, -13.056397225147862], [1558742400000, -13.480343168210311], [1558828800000, -2.7670806058887933], [1558915200000, -2.7807450809023635], [1559001600000, -1.991880623163297], [1559088000000, -7.4061771939400955], [1559174400000, -11.291016161859659], [1559260800000, -14.086840493366537], [1559347200000, -14.605808401056947], [1559433600000, -8.793707725078207], [1559520000000, -21.8777761117899], [1559606400000, -30.803810381793085], [1559692800000, -35.173846781121426], [1559779200000, -30.68118507311374], [1559865600000, -33.06123040690562], [1559952000000, -35.814126999879846], [1560038400000, -40.181700203109585], [1560124800000, -35.98487879087497], [1560211200000, -39.69716470530173], [1560297600000, -39.66835500181881], [1560384000000, -32.58530998563202], [1560470400000, -30.334641150732836], [1560556800000, -27.932960128665627], [1560643200000, -21.653403837269508], [1560729600000, -20.095628366284387], [1560816000000, -22.230658842562065], [1560902400000, -24.231366288101867], [1560988800000, -16.661146583023566], [1561075200000, -11.44392807544611], [1561161600000, -5.808989403650855], [1561248000000, 1.1508356286201433], [1561334400000, 0.6572967142712116], [1561420800000, 11.115638329944517], [1561507200000, 17.76420316136253], [1561593600000, 4.129137782586156], [1561680000000, 13.926878580873165], [1561766400000, 11.13698565074958], [1561852800000, 3.759768634203823], [1561939200000, -0.6114094927000338], [1562025600000, 6.472477404632713], [1562112000000, 15.34114056753819], [1562198400000, 5.999229512706819], [1562284800000, 3.554718130408304], [1562371200000, 6.6874470402448765], [1562457600000, 11.449900707583339], [1562544000000, 15.396183795525417], [1562630400000, 23.197494146274977], [1562716800000, 16.52048898655994], [1562803200000, 6.34172182468302], [1562889600000, 10.542265228449338], [1562976000000, 7.879352461698971], [1563062400000, -4.294927215458159], [1563148800000, 1.6898827779376404], [1563235200000, -11.377333945044683], [1563321600000, -8.015412962412825], [1563408000000, 0.4928581626029995], [1563494400000, -0.6996963167408126], [1563580800000, 3.6036633525614263], [1563667200000, 0.4573432110932174], [1563753600000, -5.2093254762922925], [1563840000000, -8.527597545162592], [1563926400000, -8.137072552966913], [1564012800000, -8.409733946090626], [1564099200000, -9.87442810268928], [1564185600000, -12.842195317707763], [1564272000000, -13.3724270640256], [1564358400000, -17.300333088007392], [1564444800000, -13.378401195552442], [1564531200000, -3.3667107586701093], [1564617600000, 0.14914640898990683], [1564704000000, 0.3620067010720902], [1564790400000, 5.499140278843413], [1564876800000, 5.766292471983775], [1564963200000, 9.58852061305933], [1565049600000, 8.158617059706813], [1565136000000, 17.71729543362372], [1565222400000, 17.885087953455184], [1565308800000, 16.30975444047212], [1565395200000, 11.893991974952883], [1565481600000, 13.628573370857168], [1565568000000, 8.617374317115775], [1565654400000, 4.665556906789334], [1565740800000, -1.2440141162277598], [1565827200000, 1.9833135790745473], [1565913600000, 2.207663080111871], [1566000000000, 0.8178956392161751], [1566086400000, 1.8785655451754906], [1566172800000, 5.983501936298296], [1566259200000, 5.1685149173735], [1566345600000, -0.20409927212870116], [1566432000000, -0.7617471127993269], [1566518400000, 3.376166213555365], [1566604800000, 0.49306627906091194], [1566691200000, 0.14932254961797753], [1566777600000, 2.2424448426672257], [1566864000000, 4.3234600504019625], [1566950400000, -0.5105033287754566], [1567036800000, -2.772333638339603], [1567123200000, -1.0397360327061733], [1567209600000, -0.6043289429836136], [1567296000000, 2.0289900346743366], [1567382400000, 9.38040062236044], [1567468800000, 16.569264270078634], [1567555200000, 16.217610995391595], [1567641600000, 17.05001872527012], [1567728000000, 14.672734145282249], [1567814400000, 17.042655918856923], [1567900800000, 18.342829642188434], [1567987200000, 15.722005271916657], [1568073600000, 17.705207674218656], [1568160000000, 16.899889087675035], [1568246400000, 21.59517170879272], [1568332800000, 22.352135985627825], [1568419200000, 22.53647897997746], [1568505600000, 23.96237479722805], [1568592000000, 21.635895226356183], [1568678400000, 25.68044830978343], [1568764800000, 24.463193551590933], [1568851200000, 27.612331208847763], [1568937600000, 28.024137181503903], [1569024000000, 25.618413178963237], [1569110400000, 27.11010105209965], [1569196800000, 20.2770988554027], [1569283200000, 5.958135145458641], [1569369600000, 5.882422304350428], [1569456000000, 0.08413842052829068], [1569542400000, -1.0745661010585081], [1569628800000, -2.9836324032652897], [1569715200000, -6.4279723327318266], [1569801600000, -2.8024637287416], [1569888000000, -1.5779068135268517], [1569974400000, 2.0765991478920114], [1570060800000, -0.4262170106915164], [1570147200000, -5.796674453076889], [1570233600000, -8.161548960939172], [1570320000000, -15.354885350637346], [1570406400000, -8.956129805774253], [1570492800000, -8.106952822204562], [1570579200000, 2.592888934139239], [1570665600000, 3.0318098295427376], [1570752000000, -5.882582339832993], [1570838400000, -7.703162786030077], [1570924800000, -10.687900600355874], [1571011200000, -7.893113601916866], [1571097600000, -10.981798793349014], [1571184000000, -10.17044034685324], [1571270400000, -7.769055917055482], [1571356800000, -13.312881353479384], [1571443200000, -15.876515515940298], [1571529600000, -12.609310274215602], [1571616000000, -10.103157223790731], [1571702400000, -13.850048458129606], [1571788800000, -23.341187994351287], [1571875200000, -20.915158185960138], [1571961600000, 4.567172256381411], [1572048000000, 12.253469138564839], [1572134400000, 17.787922343580334], [1572220800000, 14.135125215913405], [1572307200000, 16.971856810467983], [1572393600000, 11.803865471031457], [1572480000000, 15.205458164139316], [1572566400000, 18.961161287641943], [1572652800000, 20.05252432222761], [1572739200000, 21.057630476577913], [1572825600000, 25.52326453445025], [1572912000000, 24.01429699997692], [1572998400000, 23.30834398591267], [1573084800000, 23.49177734230682], [1573171200000, 17.312465435904357], [1573257600000, 18.86593088863691], [1573344000000, 24.981629331143267], [1573430400000, 21.96635856453537], [1573516800000, 24.029116860520446], [1573603200000, 22.363743980211098], [1573689600000, 21.941591594097588], [1573776000000, 18.25219111170577], [1573862400000, 20.685105702782323], [1573948800000, 23.607310691478858], [1574035200000, 19.920027664110876], [1574121600000, 21.076605901884136], [1574208000000, 15.242601471824173], [1574294400000, 6.864996003313081], [1574380800000, -3.157900811635386], [1574467200000, 0.2976846224980818], [1574553600000, -10.509768414570885], [1574640000000, -1.7968546086251536], [1574726400000, 1.5859656246155396], [1574812800000, 6.384942795645202], [1574899200000, 4.274577352031258], [1574985600000, 9.15193272483333], [1575072000000, 6.432929274557296], [1575158400000, 0.5625510083465883], [1575244800000, 2.691215512638223], [1575331200000, 5.441740557389835], [1575417600000, -0.3705824985437971], [1575504000000, 5.989067701348915], [1575590400000, 6.15966581496167], [1575676800000, 6.101145708432341], [1575763200000, 3.9416141275356154], [1575849600000, 1.249967714265722], [1575936000000, -0.8022786823715933], [1576022400000, -4.403278960562773], [1576108800000, -1.6359566413066773], [1576195200000, -4.543530474736372], [1576281600000, -8.062798518547368], [1576368000000, -9.930698864577948], [1576454400000, -15.241471140701663], [1576540800000, -25.84883528233786], [1576627200000, -9.388592552329044], [1576713600000, -9.713584691084918], [1576800000000, -13.41063588861499], [1576886400000, -14.15039735670183], [1576972800000, -6.878221535496948], [1577059200000, -11.416559462805708], [1577145600000, -17.57757249877119], [1577232000000, -18.138520027794414], [1577318400000, -14.283209208397182], [1577404800000, -17.83612092938762], [1577491200000, -15.55613578518205], [1577577600000, -14.748743020174686], [1577664000000, -20.844755890509532], [1577750400000, -28.679327588400668], [1577836800000, -27.444214439263874], [1577923200000, -30.822134590480573], [1578009600000, -24.374227480606578], [1578096000000, -23.110748365689005], [1578182400000, -23.84120391142858], [1578268800000, -16.1151421501379], [1578355200000, -13.417128253950466], [1578441600000, -16.270712403306618], [1578528000000, -20.149455027252145], [1578614400000, -13.897739660786499], [1578700800000, -16.902249332404608], [1578787200000, -14.99273686328803], [1578873600000, -16.13209392729175], [1578960000000, -7.463473778412435], [1579046400000, -8.655257074088354], [1579132800000, -9.809240184217458], [1579219200000, -7.351867954352798], [1579305600000, -5.922059088685472], [1579392000000, -10.64860803494605], [1579478400000, -11.134870741505068], [1579564800000, -13.614055874320059], [1579651200000, -14.080360259436844], [1579737600000, -19.24537896969133], [1579824000000, -18.89787758108622], [1579910400000, -19.3506474992501], [1579996800000, -16.7910023705482], [1580083200000, -9.728825273738238], [1580169600000, -4.007162787303059], [1580256000000, -3.507620967130663], [1580342400000, -0.95923556013949], [1580428800000, -3.4149931786340346], [1580515200000, -1.1023083635309092], [1580601600000, -3.4879680668382207], [1580688000000, -3.024941523140427], [1580774400000, -5.4903828081962445], [1580860800000, 3.5353057174802984], [1580947200000, 4.406624379760103], [1581033600000, 4.504566160930011], [1581120000000, 8.498331667293314], [1581206400000, 13.868893356812436], [1581292800000, 11.139829267962341], [1581379200000, 16.31930563406587], [1581465600000, 20.444355704596347], [1581552000000, 40.267966409600206], [1581638400000, 34.02953389138966], [1581724800000, 35.028086138144346], [1581811200000, 35.910916951006726], [1581897600000, 36.61268372981283], [1581984000000, 40.980473873433056], [1582070400000, 34.98119616855482], [1582156800000, 49.523327553062046], [1582243200000, 43.1192677236408], [1582329600000, 48.89123608984448], [1582416000000, 57.01747139050843], [1582502400000, 50.5943205055932], [1582588800000, 42.10070431547476], [1582675200000, 34.21746329642019], [1582761600000, 48.7939826017066], [1582848000000, 41.88132138188524], [1582934400000, 45.56292282502727], [1583020800000, 53.01545200159137], [1583107200000, 53.32799286105143], [1583193600000, 46.30472899218745], [1583280000000, 44.29517021939637], [1583366400000, 62.99696974623248], [1583452800000, 59.47108543720174], [1583539200000, 60.4932079358951], [1583625600000, 51.52128603291817], [1583712000000, 40.44718271013204], [1583798400000, 35.340297809652554], [1583884800000, 33.47302440210831], [1583971200000, -63.170331549804985], [1584057600000, -28.348069761676186], [1584144000000, -45.96851400444899], [1584230400000, -32.472307857521685], [1584316800000, -57.771302001643676], [1584403200000, -46.47326512733832], [1584489600000, -43.945556330652835], [1584576000000, -21.309350964739338], [1584662400000, -14.944773716699729], [1584748800000, -16.499708302064732], [1584835200000, -24.14621744189384], [1584921600000, -8.863402410354865], [1585008000000, -1.52777759441409], [1585094400000, -5.960746884757043], [1585180800000, -9.701776440711512], [1585267200000, -16.582061870709197], [1585353600000, -22.689389506605437], [1585440000000, -33.873518091009885], [1585526400000, -19.605818365104028], [1585612800000, -18.318116901402732], [1585699200000, -17.161906442069494], [1585785600000, -17.50289814322616], [1585872000000, -17.00998620152916], [1585958400000, -15.816407584448541], [1586044800000, -18.06823000879598], [1586131200000, -3.3012817957915104], [1586217600000, -7.066604033442047], [1586304000000, -8.294962114584223], [1586390400000, -16.810175029429217], [1586476800000, -26.208794864259346], [1586563200000, -27.136970347747706], [1586649600000, -23.495403831086662], [1586736000000, -22.783861720975153], [1586822400000, -23.735017313010076], [1586908800000, -38.16311575000765], [1586995200000, -31.844483815449678], [1587081600000, -32.36804495707685], [1587168000000, -27.42872494081888], [1587254400000, -28.959869477958932], [1587340800000, -35.64085700144523], [1587427200000, -36.86529606304447], [1587513600000, -35.925134002400455], [1587600000000, -30.41037596252289], [1587686400000, -29.02656959784474], [1587772800000, -28.29771822128521], [1587859200000, -21.418043611348764], [1587945600000, -19.874920439349864], [1588032000000, -21.84568947480716], [1588118400000, -7.168754806180516], [1588204800000, -13.278278322697616], [1588291200000, -8.204451068423879], [1588377600000, -6.346706971915552], [1588464000000, -3.0672389325710583], [1588550400000, -5.902761858214603], [1588636800000, -2.6735836789489156], [1588723200000, -3.5706182398510293], [1588809600000, 5.454082833675784], [1588896000000, 5.357777336458099], [1588982400000, 0.7595011304194941], [1589068800000, -9.036970942617017], [1589155200000, -14.787218380914908], [1589241600000, -8.876191298473543], [1589328000000, -3.147918602563493], [1589414400000, 4.6898676199958516], [1589500800000, -1.3881648982972763], [1589587200000, -1.500482855567725], [1589673600000, 4.765137254408501], [1589760000000, 2.0506500121706495], [1589846400000, 4.68294350262363], [1589932800000, -0.4962567881849509], [1590019200000, -5.9083364071710776], [1590105600000, -3.7269803021275436], [1590192000000, -4.7564780612788695], [1590278400000, -10.251483185838026], [1590364800000, -11.48837096817445], [1590451200000, -10.383279453829402], [1590537600000, -4.795932895668244], [1590624000000, 2.0853395106797734], [1590710400000, 0.5367953513981547], [1590796800000, 4.1469788636493945], [1590883200000, 1.0605087604291725], [1590969600000, 8.211614843021067], [1591056000000, 0.1647333221179963], [1591142400000, 2.539973572275727], [1591228800000, 6.981467905457492], [1591315200000, 4.868893248938633], [1591401600000, 5.520076516810747], [1591488000000, 6.977352385261298], [1591574400000, 4.6479506819192125], [1591660800000, 4.981492680214615], [1591747200000, 6.6472418568802425], [1591833600000, 0.41375585691554306], [1591920000000, 3.4514413448794983], [1592006400000, 3.831198791351113], [1592092800000, 1.8191346287481736], [1592179200000, 0.8828316619716929], [1592265600000, 2.7420989639285835], [1592352000000, 2.2103161158236446], [1592438400000, 2.731554887695239], [1592524800000, 1.8203692948268326], [1592611200000, 2.943201621733408], [1592697600000, 1.5349117775780314], [1592784000000, 5.883293228229235], [1592870400000, 4.701447633438647], [1592956800000, -0.7549060249308468], [1593043200000, -0.32525893728706023], [1593129600000, -1.407868432666703], [1593216000000, -4.161428053417183], [1593302400000, -3.4072677901633597], [1593388800000, -5.886801718161649], [1593475200000, -6.844276404416661], [1593561600000, -6.721583808285743], [1593648000000, -8.103416741170975], [1593734400000, -9.05890538120073], [1593820800000, -9.381467373789633], [1593907200000, -9.616661250440302], [1593993600000, -8.910947097169526], [1594080000000, -10.572808750526718], [1594166400000, -10.072752131464938], [1594252800000, -12.794834756284445], [1594339200000, -12.20001975654688], [1594425600000, -14.785558661467462], [1594512000000, -12.935873962667301], [1594598400000, -17.31757757117589], [1594684800000, -16.403803694099196], [1594771200000, -19.752564761565452], [1594857600000, -21.326277666321033], [1594944000000, -20.95786456569087], [1595030400000, -22.68272225530697], [1595116800000, -21.143742637122358], [1595203200000, -26.310789930462875], [1595289600000, -21.15584138808444], [1595376000000, -20.938236491879394], [1595462400000, -20.681336057723854], [1595548800000, -20.94725749561158], [1595635200000, -20.80592760991817], [1595721600000, -16.27697894094834], [1595808000000, -6.554034189780026], [1595894400000, -4.835677019361384], [1595980800000, -4.658223100267861], [1596067200000, -5.059290724314366], [1596153600000, -2.238388174533185], [1596240000000, 0.9859977932702293], [1596326400000, -6.005014211420388], [1596412800000, -5.705386111146993], [1596499200000, -3.9618169322643837], [1596585600000, 1.734864792174477], [1596672000000, 4.5495021505879265], [1596758400000, 2.641334321675771], [1596844800000, 4.4899571811058365], [1596931200000, 2.949592440730356], [1597017600000, 3.5266023577937347], [1597104000000, 0.9347160714275162], [1597190400000, 3.4543762616762876], [1597276800000, 8.11430120892652], [1597363200000, 7.306914202409757], [1597449600000, 8.50843046841004], [1597536000000, 8.561365174590065], [1597622400000, 10.248138170502415], [1597708800000, 8.333253547285466], [1597795200000, 6.852218455431938], [1597881600000, 10.744356603874053], [1597968000000, 6.557159363645496], [1598054400000, 8.230257157183985], [1598140800000, 8.003498725263569], [1598227200000, 9.057880872570252], [1598313600000, 4.936780141989999], [1598400000000, 7.358489653106801], [1598486400000, 7.579984629154296], [1598572800000, 8.5843897946406], [1598659200000, 8.340872220040268], [1598745600000, 10.678080364680852], [1598832000000, 10.440042773694842], [1598918400000, 12.419544940338426], [1599004800000, 8.198294153953697], [1599091200000, -5.140967084119154], [1599177600000, -1.8652645701096162], [1599264000000, -5.611692640017083], [1599350400000, -4.334136847251898], [1599436800000, -2.7745149377481653], [1599523200000, -5.962110946368512], [1599609600000, -4.495649470686146], [1599696000000, -4.756509519472928], [1599782400000, -4.242105586509098], [1599868800000, -4.659099999248895], [1599955200000, -6.103960881812611], [1600041600000, -1.6800652311745239], [1600128000000, -0.5311073122548464], [1600214400000, 1.8895135122077704], [1600300800000, 0.043771974386430657], [1600387200000, 0.30817408254347356], [1600473600000, 1.0021062785736206], [1600560000000, -1.4512664118617806], [1600646400000, -7.5089934974290315], [1600732800000, -6.253440890158942], [1600819200000, -11.118452041151869], [1600905600000, -6.559866973009747], [1600992000000, -6.746199609542288], [1601078400000, -7.251564672631133], [1601164800000, -7.439938668255053], [1601251200000, -9.484094623108547], [1601337600000, -8.61605475479189], [1601424000000, -10.509710894613903], [1601510400000, -13.475982920705263], [1601596800000, -13.926927754956978], [1601683200000, -15.515019928734347], [1601769600000, -14.534564298859692], [1601856000000, -13.972862650392017], [1601942400000, -17.598171864109617], [1602028800000, -18.204072455581837], [1602115200000, -18.3122049097166], [1602201600000, -16.742009685073498], [1602288000000, -14.35092181578392], [1602374400000, -14.616936267896875], [1602460800000, -13.264882052688591], [1602547200000, -16.16955739199082], [1602633600000, -17.9217386088705], [1602720000000, -20.36918585680891], [1602806400000, -22.06463793721639], [1602892800000, -21.163301593629626], [1602979200000, -20.366556805305606], [1603065600000, -18.682144469900578], [1603152000000, -19.849213589944043], [1603238400000, -13.33102064593001], [1603324800000, -14.974587461129545], [1603411200000, -16.250373036482955], [1603497600000, -14.145844321108228], [1603584000000, -15.113334899489558], [1603670400000, -15.221142880082567], [1603756800000, -13.724723986083802], [1603843200000, -16.421348175157732], [1603929600000, -16.48793114436009], [1604016000000, -16.564135926165932], [1604102400000, -14.468710575919289], [1604188800000, -15.590148711700465], [1604275200000, -18.54680656533833], [1604361600000, -16.655058720063835], [1604448000000, -16.444940806718563], [1604534400000, -8.432594118814109], [1604620800000, -8.596676548062675], [1604707200000, -13.027561656421511], [1604793600000, -10.004339614132476], [1604880000000, -12.56286449405323], [1604966400000, -12.833149873229274], [1605052800000, -11.240289397219982], [1605139200000, -7.116758626115143], [1605225600000, -6.9066601187186905], [1605312000000, -9.665241869957526], [1605398400000, -10.798388559138914], [1605484800000, -8.62452451679502], [1605571200000, -4.253204673885193], [1605657600000, -5.383826052139511], [1605744000000, -4.643461590846201], [1605830400000, -1.0562326742365258], [1605916800000, -2.9308934048293906], [1606003200000, -4.511649696291144], [1606089600000, -5.387719748097112], [1606176000000, -2.183842145944624], [1606262400000, -5.122070715014701], [1606348800000, -11.697202875032076], [1606435200000, -11.622997482420814], [1606521600000, -11.603374678108977], [1606608000000, -10.146805864861832], [1606694400000, -5.224921015165677], [1606780800000, -8.138614731076714], [1606867200000, -8.523811780951945], [1606953600000, -8.734360041689541], [1607040000000, -11.820264896872203], [1607126400000, -12.888038267571702], [1607212800000, -12.439269809521491], [1607299200000, -12.773216412120235], [1607385600000, -16.94287504211505], [1607472000000, -18.396416774369584], [1607558400000, -21.080445534218114], [1607644800000, -22.834025605110327], [1607731200000, -22.109423129296246], [1607817600000, -20.557443391929098], [1607904000000, -19.296321948554862], [1607990400000, -19.677309113767237], [1608076800000, -16.035083051687536], [1608163200000, -13.716458894939905], [1608249600000, -13.392411713625606], [1608336000000, -13.297584789896575], [1608422400000, -13.802402697713717], [1608508800000, -15.034814401298192], [1608595200000, -12.869204974467365], [1608681600000, -15.933952223118055], [1608768000000, -14.596350194062552], [1608854400000, -13.155097610772714], [1608940800000, -10.472567346370425], [1609027200000, -10.657071203775075], [1609113600000, -8.692906613144515], [1609200000000, -8.296454816409096], [1609286400000, -6.762016954666251], [1609372800000, -7.145969340022617], [1609459200000, -7.133676756064844], [1609545600000, -3.251000976458812], [1609632000000, -1.6532216757517801], [1609718400000, -2.4716294225518993], [1609804800000, -0.40816838028057134], [1609891200000, 1.6615054671768377], [1609977600000, 3.9039554176133464], [1610064000000, 4.1208900212700925], [1610150400000, 4.0512253294429], [1610236800000, 2.8939698410513444], [1610323200000, -0.8755423028288192], [1610409600000, -2.6469863748763913], [1610496000000, 0.8236609898131917], [1610582400000, 2.3101339916353396], [1610668800000, -0.5890295126826999], [1610755200000, -1.1796551398292152], [1610841600000, -1.201114440853118], [1610928000000, -1.7308665575567943], [1611014400000, -3.041182954762199], [1611100800000, -3.388826862120517], [1611187200000, -9.35263663010825], [1611273600000, -7.737178009502671], [1611360000000, -8.882578063522232], [1611446400000, -8.634549242318705], [1611532800000, -9.552641367277808], [1611619200000, -9.362699055524395], [1611705600000, -12.461380815043547], [1611792000000, -8.940176973933141], [1611878400000, -8.65874557636647], [1611964800000, -8.728997258562302], [1612051200000, -10.032458564162539], [1612137600000, -10.993128550915621], [1612224000000, -8.533889063729866], [1612310400000, -7.111402941486276], [1612396800000, -7.479150000748838], [1612483200000, -6.713328227007054], [1612569600000, -5.948194645832942], [1612656000000, -6.678353822455264], [1612742400000, -2.1753930023743777], [1612828800000, -1.8386275900560705], [1612915200000, -3.4948602042791777], [1613001600000, -1.3579451150474426], [1613088000000, -1.9805480737290466], [1613174400000, -2.405102168430659], [1613260800000, -1.7671281190668893], [1613347200000, -2.2336053479850975], [1613433600000, -1.2889077395532524], [1613520000000, -0.5398198274867596], [1613606400000, -0.2787119562331597], [1613692800000, 1.5127534247072845], [1613779200000, 1.1791129308989312], [1613865600000, 1.8657622292593743], [1613952000000, 0.5090390339315434], [1614038400000, -2.015516613954361], [1614124800000, -1.8939914448126274], [1614211200000, -2.917903094764206], [1614297600000, -3.7336315015148287], [1614384000000, -4.220176635357383], [1614470400000, -4.726692819816961], [1614556800000, -2.213334244659862], [1614643200000, -3.2443537635569584], [1614729600000, -2.4087350436047714], [1614816000000, -3.3201531670214095], [1614902400000, -3.506818376975822], [1614988800000, -3.687844415495263], [1615075200000, -2.5874369008031124], [1615161600000, -1.612077183609017], [1615248000000, -0.7491006361266201], [1615334400000, -0.169301164242178], [1615420800000, 0.5396024115604732], [1615507200000, -0.08967357234963913], [1615593600000, 1.1432366999716308], [1615680000000, 0.40433432293865224], [1615766400000, -0.6881711772501049], [1615852800000, -0.5420973454106033], [1615939200000, 0.5692893793551264], [1616025600000, 0.04163312901946625], [1616112000000, -0.0821444442451309], [1616198400000, -0.0132026628098032], [1616284800000, -0.046641425673740855], [1616371200000, -1.438527419921435], [1616457600000, -1.6969567174767022], [1616544000000, -2.048327239610117], [1616630400000, -2.4495855894701535], [1616716800000, -0.7671901700539294], [1616803200000, -0.2156683255223939], [1616889600000, 0.07936597443036675], [1616976000000, 0.19207749626213655], [1617062400000, 0.22447956143959402], [1617148800000, 0.7266188216106144], [1617235200000, 0.8397775566470145], [1617321600000, 0.7283416091467814], [1617408000000, 0.15412406190993266], [1617494400000, 1.0815387168029602], [1617580800000, 0.8595102689594682], [1617667200000, 0.4079567102987127], [1617753600000, -0.4052148611847599], [1617840000000, 0.7659602376887236], [1617926400000, 0.4960557306345379], [1618012800000, 1.1355921311287673], [1618099200000, 1.7997832782709366], [1618185600000, 1.4371277129994553], [1618272000000, 2.68023073283355], [1618358400000, 3.12359532704032], [1618444800000, 3.61459136086129], [1618531200000, 2.643250879464233], [1618617600000, 2.580987717350105], [1618704000000, 1.5998255088720725], [1618790400000, 1.4373567963834262], [1618876800000, 2.0336834096687113], [1618963200000, 2.488991384765562], [1619049600000, 1.0890813470756413], [1619136000000, 0.9778525184026492], [1619222400000, 0.7156150072415386], [1619308800000, 1.0624844889250937], [1619395200000, 2.90322717098487], [1619481600000, 3.7761871300787178], [1619568000000, 4.983888419839026], [1619654400000, 3.955579016128546], [1619740800000, 6.614868532947057], [1619827200000, 7.11404363650162], [1619913600000, 7.145792859132861], [1620000000000, 6.749493964284177], [1620086400000, 5.495538789831521], [1620172800000, 8.591676402834253], [1620259200000, 7.276546673077675], [1620345600000, 9.268951995843864], [1620432000000, 10.69557033541166], [1620518400000, 10.825220762717315], [1620604800000, 9.686236270893922], [1620691200000, 10.365675480538961], [1620777600000, 7.240829146540648], [1620864000000, 6.566513140638328], [1620950400000, 8.198236005437387], [1621036800000, 7.5644632060513715], [1621123200000, 7.0029702696955525], [1621209600000, 4.360015531016543], [1621296000000, 4.273303214788015], [1621382400000, -1.1194264126478117], [1621468800000, 1.8481371571785132], [1621555200000, 0.7905622689074434], [1621641600000, 1.9059157631377772], [1621728000000, -1.5878004586330547], [1621814400000, 2.83591942149193], [1621900800000, 2.478159141776608], [1621987200000, 2.107284674487964], [1622073600000, 1.172667731651174], [1622160000000, 0.3924921081855359], [1622246400000, -0.05294766596450984], [1622332800000, -0.48954084463532155], [1622419200000, 2.2346685781370255], [1622505600000, 1.2580298547348576], [1622592000000, 1.31968813277431], [1622678400000, 2.939698447370972], [1622764800000, 2.1292021079922634], [1622851200000, 1.01260405628517], [1622937600000, -0.25096366851988705], [1623024000000, -1.199097291580287], [1623110400000, -2.0207867554317005], [1623196800000, 1.9643670450095172], [1623283200000, 1.8108531776403183], [1623369600000, 3.3337264976449674], [1623456000000, 1.5045850543355357], [1623542400000, 3.4231982052136374], [1623628800000, 6.259233926137064], [1623715200000, 5.386389844030624], [1623801600000, 3.990544817087354], [1623888000000, 4.435687985847302], [1623974400000, 3.1677471098730194], [1624060800000, 2.4984541984983792], [1624147200000, 1.5605989646795138], [1624233600000, -1.4554523359353055], [1624320000000, -0.5071937518277849], [1624406400000, 0.2454687083668574], [1624492800000, 2.0492004506658787], [1624579200000, -1.6865797070319957], [1624665600000, -1.227720284412655], [1624752000000, 0.5807383569241011], [1624838400000, 0.9071384133221869], [1624924800000, 2.074174374959057], [1625011200000, 0.5683316174173143], [1625097600000, -0.43367993052684994], [1625184000000, -1.0036479886660317], [1625270400000, -0.14770821355837427], [1625356800000, 0.18349407475365354], [1625443200000, -1.0564155677367921], [1625529600000, -0.35011771317202545], [1625616000000, -1.8195983201977413], [1625702400000, -2.8444449771243825], [1625788800000, -2.7988640639459987], [1625875200000, -3.4359784950905663], [1625961600000, -2.638008868324647], [1626048000000, -4.166682656140978], [1626134400000, -4.364661623424766], [1626220800000, -5.363357577549806], [1626307200000, -6.4978239186285265], [1626393600000, -8.543804044646222], [1626480000000, -8.584285679246534], [1626566400000, -8.13849699110014], [1626652800000, -9.748946601173756], [1626739200000, -11.044908654553765], [1626825600000, -8.619937606001812], [1626912000000, -8.766901451872094], [1626998400000, -8.828688479955545], [1627084800000, -8.178252132165504], [1627171200000, -6.791802113761072], [1627257600000, -5.23582247201022], [1627344000000, -2.819561235861677], [1627430400000, -2.8839847478108425], [1627516800000, -2.9392315136293945], [1627603200000, -2.825501604735294], [1627689600000, -3.418415740695913], [1627776000000, -4.441359429790921], [1627862400000, -4.971499609507589], [1627948800000, -5.247082433381976], [1628035200000, -4.442143427002009], [1628121600000, -3.53380177824738], [1628208000000, -3.3923732511866618], [1628294400000, -2.1518165543687857], [1628380800000, -2.8459095929294023], [1628467200000, -1.2019092423230546], [1628553600000, -0.5238717607064274], [1628640000000, -0.8188215656916356], [1628726400000, -1.5697249718192197], [1628812800000, -0.20019509013622638], [1628899200000, -0.5316968110755056], [1628985600000, -0.9392416180777587], [1629072000000, -1.264521513252575], [1629158400000, -1.3744935517543837], [1629244800000, -1.7523551852585442], [1629331200000, -0.4062598478103112], [1629417600000, 0.7831504499064792], [1629504000000, 0.4177132293855905], [1629590400000, 0.44000202015122625], [1629676800000, 1.4432786982580055], [1629763200000, 1.2802163391224894], [1629849600000, 1.2236753795638649], [1629936000000, -0.09111225113020538], [1630022400000, 1.5177475859077916], [1630108800000, 1.2943277328295792], [1630195200000, 0.9655717171868332], [1630281600000, 0.8913439158356624], [1630368000000, 1.914381212280965], [1630454400000, 2.182599389818833], [1630540800000, 1.8431454086820125], [1630627200000, 2.1750523682953187], [1630713600000, 2.0461714707099716], [1630800000000, 2.734120236187522], [1630886400000, 3.9153142031158055], [1630972800000, 1.2033454681934117], [1631059200000, -0.2755055343097439], [1631145600000, -0.4612903608984169], [1631232000000, -1.5520880166169846], [1631318400000, -1.5189248231263477], [1631404800000, -1.0168268329930328], [1631491200000, -1.2315600504279942], [1631577600000, 0.37841340659266365], [1631664000000, -0.15958169632342134], [1631750400000, -0.7561632521513033], [1631836800000, -1.644428376274604], [1631923200000, -1.0892230804241763], [1632009600000, -1.7923521659425674], [1632096000000, -4.504891017887111], [1632182400000, -6.056085998069172], [1632268800000, -4.906354263422472], [1632355200000, -4.082072463611773], [1632441600000, -6.139893483497858], [1632528000000, -6.242117453280798], [1632614400000, -6.002983251519005], [1632700800000, -7.229948294109072], [1632787200000, -8.052130726891605], [1632873600000, -8.20231658090664], [1632960000000, -6.519145312507199], [1633046400000, -4.531538518889903], [1633132800000, -4.835190673685396], [1633219200000, -4.500801308646359], [1633305600000, -4.427809451168663], [1633392000000, -3.409987969794834], [1633478400000, -1.925307542347987], [1633564800000, -2.3250600641096923], [1633651200000, -2.5897014825792013], [1633737600000, -2.190822593561272], [1633824000000, -2.397676915573136], [1633910400000, -1.8359331383261122], [1633996800000, -2.451917483027678], [1634083200000, -1.775920610884583], [1634169600000, -1.5749115144901324], [1634256000000, -0.09725833857103083], [1634342400000, -0.4197044346875387], [1634428800000, -0.35247523881505316], [1634515200000, -0.48795485314580134], [1634601600000, 0.49962759586655636], [1634688000000, 1.2575458597262497], [1634774400000, 0.4434167198687433], [1634860800000, -0.1933552367555933], [1634947200000, -0.1646235031170349], [1635033600000, -0.3802033087217964], [1635120000000, 0.36964171688256897], [1635206400000, -0.44925989331751026], [1635292800000, -0.8819053987171372], [1635379200000, 0.06586765681790752], [1635465600000, 1.018405511891956], [1635552000000, 0.6110815833516696], [1635638400000, 0.09775944025557948], [1635724800000, -0.011976718219656846], [1635811200000, 0.9387946299622456], [1635897600000, 0.9681753096324712], [1635984000000, 0.7321364361600331], [1636070400000, 1.2820352433535476], [1636156800000, 1.6670153620688168], [1636243200000, 1.9456485061037085], [1636329600000, 3.257269727964932], [1636416000000, 3.3199775262894207], [1636502400000, 2.7926074674910097], [1636588800000, 3.3099190833292553], [1636675200000, 3.8132127509938343], [1636761600000, 3.857999857217166], [1636848000000, 3.9052001054167036], [1636934400000, 3.83665337987987], [1637020800000, 2.526789574169918], [1637107200000, 2.5730831468446524], [1637193600000, 1.8372124808556904], [1637280000000, 3.2398343130617064], [1637366400000, 3.7969427647241503], [1637452800000, 3.1285176885800112], [1637539200000, 2.511887249844463], [1637625600000, 2.5648808947081747], [1637712000000, 2.3955031893638363], [1637798400000, 3.314536341735831], [1637884800000, 1.9513644558040824], [1637971200000, 2.5095452682490134], [1638057600000, 3.306244815236454], [1638144000000, 3.752187689033086], [1638230400000, 3.3591437975761522], [1638316800000, 3.576306003805861], [1638403200000, 3.4848496600368577], [1638489600000, 2.7669988152517746], [1638576000000, 0.32488967518972345], [1638662400000, 0.38322593989619236], [1638748800000, 1.389676536322952], [1638835200000, 1.4276151166717455], [1638921600000, 1.8336927007600465], [1639008000000, 0.30008701315417596], [1639094400000, 0.6571464688683974], [1639180800000, 1.4742730820384864], [1639267200000, 1.8107185337408538], [1639353600000, 0.2501987016925469], [1639440000000, 1.1584759794622599], [1639526400000, 1.740460532598192], [1639612800000, 1.0383971003209211], [1639699200000, 0.5593949936233287], [1639785600000, 0.7515861729335853], [1639872000000, 0.6478032779504233], [1639958400000, 1.0261250759617795], [1640044800000, 2.323080409114773], [1640131200000, 2.594190433677433], [1640217600000, 3.962382072900965], [1640304000000, 5.076863698102265], [1640390400000, 4.982428784614214], [1640476800000, 4.892883923920195], [1640563200000, 5.025721807211973], [1640649600000, 3.366874706241447], [1640736000000, 3.1226631069092647], [1640822400000, 3.8164399228724477], [1640908800000, 4.1975500152812515], [1640995200000, 5.201943720367424], [1641081600000, 4.731883167680515], [1641168000000, 4.223810458366714], [1641254400000, 3.6139096540649547], [1641340800000, 2.5593431711796484], [1641427200000, 2.562789070810801], [1641513600000, 1.4027584394560222], [1641600000000, 1.7517253308250957], [1641686400000, 1.4889586754740307], [1641772800000, 1.1743090930104287], [1641859200000, 1.6016158926921946], [1641945600000, 2.7787742310689296], [1642032000000, 2.089460112964659], [1642118400000, 2.5041385803955123], [1642204800000, 2.7830983573417853], [1642291200000, 2.436209543534005], [1642377600000, 1.3768205061583814], [1642464000000, 1.0313717099582078], [1642550400000, 1.0200542651710407], [1642636800000, 0.8697082705011425], [1642723200000, -3.032982120739547], [1642809600000, -4.3385469671932455], [1642896000000, -3.0051902548504117], [1642982400000, -2.789229802429645], [1643068800000, -3.1902093399077884], [1643155200000, -2.701062078458385], [1643241600000, -2.028273637343787], [1643328000000, -2.258055250169626], [1643414400000, -1.8531480657819728], [1643500800000, -1.6124295001215785], [1643587200000, -2.1429024913652626], [1643673600000, -2.742176804733802], [1643760000000, -3.869155125740967], [1643846400000, -2.8459764827126293], [1643932800000, 0.9876251633843793], [1644019200000, 0.850878759246676], [1644105600000, 2.309871562765089], [1644192000000, 2.5148553998837855], [1644278400000, 1.7634599832398692], [1644364800000, 1.7699180837913389], [1644451200000, 2.2259786189532136], [1644537600000, 2.154662336548519], [1644624000000, 1.9921034778126696], [1644710400000, 2.861498634308383], [1644796800000, 2.1946809037138735], [1644883200000, 2.916455683719228], [1644969600000, 1.8992062640028706], [1645056000000, 0.20974953006398067], [1645142400000, 0.21608079076766984], [1645228800000, 0.18463336200690605], [1645315200000, -0.2682005636633704], [1645401600000, -2.584842641615211], [1645488000000, -2.063093785906787], [1645574400000, -3.767968302201112], [1645660800000, -2.3725855483336105], [1645747200000, -1.1779010770889045], [1645833600000, -1.4188189377437013], [1645920000000, -2.2943630962694783], [1646006400000, 1.2797072630585191], [1646092800000, 1.6907185281516917], [1646179200000, 0.4763475553311096], [1646265600000, 0.08194649074080473], [1646352000000, -2.374404848095118], [1646438400000, -2.236863199391273], [1646524800000, -3.0146393291715867], [1646611200000, -3.7211760119391073], [1646697600000, -3.202319086446515], [1646784000000, -0.9461210693548594], [1646870400000, -2.671833259909519], [1646956800000, -3.3074418530538594], [1647043200000, -3.375159442059527], [1647129600000, -4.301177760699623], [1647216000000, -2.4237636942933705], [1647302400000, -2.915726886184032], [1647388800000, -1.501144243866264], [1647475200000, -1.4185215862677936], [1647561600000, -0.9340729011757389], [1647648000000, -0.6596203364069311], [1647734400000, -1.4865911524616635], [1647820800000, -1.4330889466008614], [1647907200000, -0.6580463536518195], [1647993600000, -0.10055034292530252], [1648080000000, 1.0935447400688716], [1648166400000, 1.3953300888785094], [1648252800000, 1.5836379405959988], [1648339200000, 2.9911588242494176], [1648425600000, 3.1915900489170426], [1648512000000, 3.719628521666152], [1648598400000, 3.47768669578344], [1648684800000, 2.880078356247509], [1648771200000, 3.7368097389982253], [1648857600000, 3.6656647139325287], [1648944000000, 4.0414154600598735], [1649030400000, 4.215917255527351], [1649116800000, 3.986491781479849], [1649203200000, 1.8700630195342853], [1649289600000, 2.9371466414951684], [1649376000000, 2.554600278867767], [1649462400000, 3.2573479579081592], [1649548800000, 3.1648644437889075], [1649635200000, 2.090326758282245], [1649721600000, 2.671441652360379], [1649808000000, 3.478369803266368], [1649894400000, 3.3559539929480167], [1649980800000, 4.150402421550773], [1650067200000, 4.124847184318099], [1650153600000, 3.4123899274218275], [1650240000000, 5.5873937037511965], [1650326400000, 6.175020689803745], [1650412800000, 6.709049149159341], [1650499200000, 6.131603002234186], [1650585600000, 6.162771345065551], [1650672000000, 5.927658669541586], [1650758400000, 5.46341241160907], [1650844800000, 8.104142172350493], [1650931200000, 5.873588426994736], [1651017600000, 7.62366054073842], [1651104000000, 8.217928207748535], [1651190400000, 7.9243432065571895], [1651276800000, 6.809721094855199], [1651363200000, 7.006488808982951], [1651449600000, 8.282648743206636], [1651536000000, 6.984636770621535], [1651622400000, 10.344071926383698], [1651708800000, 7.2612545020120365], [1651795200000, 7.488734801665096], [1651881600000, 6.459116158406417], [1651968000000, 4.2716668043796915], [1652054400000, -0.4776421899488099], [1652140800000, 0.3608576317119656], [1652227200000, -0.6851588485682214], [1652313600000, -1.4245860966156698], [1652400000000, 0.1648054502207117], [1652486400000, 1.174724463699846], [1652572800000, 2.9434701364845495], [1652659200000, 2.374207418365728], [1652745600000, 3.177359189351151], [1652832000000, 1.5411429470727143], [1652918400000, 4.985266450563131], [1653004800000, 4.270290064033645], [1653091200000, 5.733021719904158], [1653177600000, 6.177348394566835], [1653264000000, 5.463214988411721], [1653350400000, 6.359448145222956], [1653436800000, 7.345139437047862], [1653523200000, 7.337997379765227], [1653609600000, 6.980190736224969], [1653696000000, 8.675289818359389], [1653782400000, 9.036426064777146], [1653868800000, 13.564390748047103], [1653955200000, 14.133983140172461], [1654041600000, 12.367325226717014], [1654128000000, 13.950019048939254], [1654214400000, 13.693244657551588], [1654300800000, 15.098060693278256], [1654387200000, 14.900386779372624], [1654473600000, 18.196874105154038], [1654560000000, 18.3731666431717], [1654646400000, 17.34638710542103], [1654732800000, 17.246466789532974], [1654819200000, 16.298866358770155], [1654905600000, 16.31550993153617], [1654992000000, 13.089708802837862], [1655078400000, 5.326869753687276], [1655164800000, 5.2407583227189605], [1655251200000, 5.95597996389472], [1655337600000, -1.1048703708421073], [1655424000000, -0.6800097988744938], [1655510400000, -5.444477888817701], [1655596800000, 0.23703485430770854], [1655683200000, -0.6350071191718882], [1655769600000, 0.07553788219252056], [1655856000000, -2.7326096586287463], [1655942400000, -0.37354165060195044], [1656028800000, 0.5313586704671422], [1656115200000, 1.0889321771181386], [1656201600000, 0.5692119425469144], [1656288000000, -0.5659116875707042], [1656374400000, -1.822374663993088], [1656460800000, -4.122139372020271], [1656547200000, -6.018033110722783], [1656633600000, -7.851427882400117], [1656720000000, -7.965364225362748], [1656806400000, -6.917628991835301], [1656892800000, -3.8215991568816463], [1656979200000, -3.8413324804320155], [1657065600000, -4.26403755615884], [1657152000000, -2.0619413083707627], [1657238400000, -2.3564643427854435], [1657324800000, -2.2344353790467295], [1657411200000, -3.869055486132737], [1657497600000, -6.930535795725859], [1657584000000, -8.82052152668416], [1657670400000, -7.343613147063891], [1657756800000, -6.698764301411046], [1657843200000, -6.3388318410867015], [1657929600000, -4.9993724294047155], [1658016000000, -6.012823485105656], [1658102400000, -1.382515636350064], [1658188800000, 1.3483265345048778], [1658275200000, -0.08466885910664246], [1658361600000, -0.5092793679692704], [1658448000000, -0.6897600754572153], [1658534400000, -1.1800119025820948], [1658620800000, -0.992105427554506], [1658707200000, -4.186009970636093], [1658793600000, -3.7657555584837326], [1658880000000, 0.2811861500691606], [1658966400000, 2.2310494023198544], [1659052800000, 3.7208174780769383], [1659139200000, 3.592713225497775], [1659225600000, 2.9528998129765966], [1659312000000, 2.184562441226163], [1659398400000, 2.3155215737641157], [1659484800000, 1.7276259152350661], [1659571200000, 1.1788312544234714], [1659657600000, 4.863527493941874], [1659744000000, 4.102451643638091], [1659830400000, 4.6485297172988425], [1659916800000, 5.7702329789781], [1660003200000, 5.554378310638796], [1660089600000, 7.017203066948198], [1660176000000, 6.851375288725066], [1660262400000, 8.746220472933132], [1660348800000, 8.677688463246], [1660435200000, 8.301818536214085], [1660521600000, 7.2442954941055575], [1660608000000, 9.21479919215217], [1660694400000, 7.6284644353806215], [1660780800000, 7.517690762069236], [1660867200000, 1.3750444504256336], [1660953600000, 2.013982906414981], [1661040000000, 3.594094224419493], [1661126400000, 2.4995877691904127], [1661212800000, 5.848402081511537], [1661299200000, 5.202682559615894], [1661385600000, 5.242091754464738], [1661472000000, 0.48374449453325497], [1661558400000, -0.1361825849586893], [1661644800000, -1.1815703464703091], [1661731200000, 0.3502263120219027], [1661817600000, 1.8030207540817003], [1661904000000, 2.1354855463081748], [1661990400000, 1.8319298838338938], [1662076800000, 0.05147505940459496], [1662163200000, -0.33439424451880484], [1662249600000, 0.8515350043907688], [1662336000000, -0.9590128718636493], [1662422400000, -2.517658041987559], [1662508800000, -0.7769550594670847], [1662595200000, -1.03564035749568], [1662681600000, 5.122398533125093], [1662768000000, 6.064761943546472], [1662854400000, 7.295408149970541], [1662940800000, 7.992180941172535], [1663027200000, 2.5057124478151707], [1663113600000, 2.809683757011811], [1663200000000, 0.3487689055265406], [1663286400000, 1.3404108010563647], [1663372800000, 2.7956323460493593], [1663459200000, 0.8564796063703142], [1663545600000, 0.4772332797003287], [1663632000000, -1.7534362268437889], [1663718400000, -3.155053317955179], [1663804800000, -0.25394490277660964], [1663891200000, -0.10576817071250844], [1663977600000, -1.0328731200513772], [1664064000000, -1.6514992152657442], [1664150400000, -0.549307221075594], [1664236800000, -1.8647354415939787], [1664323200000, -1.098354180914768], [1664409600000, -0.19429101231089874], [1664496000000, -0.5364573125840053], [1664582400000, -0.8841233672118847], [1664668800000, -2.0049108285480486], [1664755200000, 0.058300184484650686], [1664841600000, 1.7818606233888659], [1664928000000, 1.1060416035250569], [1665014400000, 0.7247909638108325], [1665100800000, -1.3370542648649035], [1665187200000, -1.8687799770174394], [1665273600000, -1.8506405291275172], [1665360000000, -2.5414947943860398], [1665446400000, -1.6137829110522688], [1665532800000, 1.2744242808575592], [1665619200000, 0.5195127211682831], [1665705600000, -0.4980868552208335], [1665792000000, -0.8914437089377287], [1665878400000, 0.30726171861175544], [1665964800000, 1.3673437565669389], [1666051200000, 1.393648555460416], [1666137600000, 3.411923594351208], [1666224000000, 1.612920941546875], [1666310400000, 1.690138423455906], [1666396800000, 1.8043521614179667], [1666483200000, 4.245257752496599], [1666569600000, 4.0680543540860725], [1666656000000, 7.068776486427865], [1666742400000, 11.682907905889195], [1666828800000, 8.499540855693624], [1666915200000, 9.32077321875687], [1667001600000, 10.104548652453687], [1667088000000, 10.82797765438653], [1667174400000, 11.146181499977274], [1667260800000, 11.624066377214945], [1667347200000, 12.445843517067232], [1667433600000, 10.959572840123386], [1667520000000, 13.997341302660573], [1667606400000, 14.87738679309551], [1667692800000, 14.624670003027461], [1667779200000, 14.40453675586376], [1667865600000, 7.088604332601477], [1667952000000, -4.2662253138711606], [1668038400000, 2.697931171298819], [1668124800000, 0.6419060327537807], [1668211200000, -0.043100581145125716], [1668297600000, -1.703140303668249], [1668384000000, 0.3224237441669686], [1668470400000, 0.11415480889408514], [1668556800000, -1.7707478649577126], [1668643200000, -1.4272318722415775], [1668729600000, -0.6742280142328809], [1668816000000, -0.5128877280562563], [1668902400000, -2.4532682567617883], [1668988800000, -4.091040289409847], [1669075200000, -3.4861022764632708], [1669161600000, -2.2452239244458667], [1669248000000, -2.042780486689196], [1669334400000, -1.6651751922986477], [1669420800000, -1.8853115860001708], [1669507200000, -2.1573900766996132], [1669593600000, -2.823509769189201], [1669680000000, -2.758982346019735], [1669766400000, 0.6907996383743296], [1669852800000, -0.09688632271354436], [1669939200000, 1.2236224115317498], [1670025600000, 0.2891322973994477], [1670112000000, 1.1720787481313835], [1670198400000, 0.6541256212744031], [1670284800000, 0.341530316045521], [1670371200000, -0.6090226731973303], [1670457600000, 1.2720514565222913], [1670544000000, 1.5295687319238596], [1670630400000, 1.4308716397376315], [1670716800000, 1.0849491355430132], [1670803200000, 1.6349119552125444], [1670889600000, 3.2568561766448454], [1670976000000, 2.9629560552804435], [1671062400000, 0.47564279588237923], [1671148800000, -3.1906850071187307], [1671235200000, -3.374388112345457], [1671321600000, -3.729153497520457], [1671408000000, -5.390764441109241], [1671494400000, -3.494631964267654], [1671580800000, -3.986525439331473], [1671667200000, -5.121338191668997], [1671753600000, -7.138701175297825], [1671840000000, -7.602006857106971], [1671926400000, -7.801359182000937], [1672012800000, -7.88343088882371], [1672099200000, -8.82426652599392], [1672185600000, -10.061135313555553], [1672272000000, -10.670114833907448], [1672358400000, -12.747219884766608], [1672444800000, -13.770733273562243], [1672531200000, -13.881805991619714], [1672617600000, -13.539079606765185], [1672704000000, -13.763826517324901], [1672790400000, -13.745372779630344], [1672876800000, -14.705821545201445], [1672963200000, -16.026957489750885], [1673049600000, -16.7268958724365], [1673136000000, -16.115857062179273], [1673222400000, -15.598791556054522], [1673308800000, -14.82758201004819], [1673395200000, -13.099525400423872], [1673481600000, -9.441741490356222], [1673568000000, -7.00067034255224], [1673654400000, -4.3076300268851355], [1673740800000, -4.587382069467424], [1673827200000, -3.309294326292843], [1673913600000, -3.9678173918985777], [1674000000000, -6.694075069584855], [1674086400000, -4.401459276389716], [1674172800000, -1.0027112746694655], [1674259200000, -0.8358568075416173]], &quot;type&quot;: &quot;bar&quot;, &quot;name&quot;: &quot;outperf&quot;}, {&quot;data&quot;: [[1483228800000, 141.16954939356447], [1483315200000, 160.47933310148255], [1483401600000, 143.91124359977493], [1483488000000, 296.81983768506325], [1483574400000, 113.98740358321083], [1483660800000, -30.19941616644155], [1483747200000, -38.8034630408406], [1483833600000, -16.24123904083399], [1483920000000, -25.743187308369215], [1484006400000, -58.63076050321524], [1484092800000, -247.886646223159], [1484179200000, -204.24931349345525], [1484265600000, -186.98344224298853], [1484352000000, -213.6530426101981], [1484438400000, -201.63984601625043], [1484524800000, -196.2256342401638], [1484611200000, -99.71103752696445], [1484697600000, -147.05769043791133], [1484784000000, -111.89839006287184], [1484870400000, -128.7264147321912], [1484956800000, -100.19183322388426], [1485043200000, -91.62601537681167], [1485129600000, -99.49380869517745], [1485216000000, -172.88731621911757], [1485302400000, -178.89388966638944], [1485388800000, -152.01535074636377], [1485475200000, -162.30238655045332], [1485561600000, -164.7708686317028], [1485648000000, -166.42759654131396], [1485734400000, -170.86629152364958], [1485820800000, -133.32969363172833], [1485907200000, -121.22376268392327], [1485993600000, -98.79724735580339], [1486080000000, -104.61338754620874], [1486166400000, -78.51910739334971], [1486252800000, -97.56053082911785], [1486339200000, -99.64752211585437], [1486425600000, -78.6431393334492], [1486512000000, -61.95208366351517], [1486598400000, -180.37299092369813], [1486684800000, -151.86221889740273], [1486771200000, -145.81664382628014], [1486857600000, -173.6033517292435], [1486944000000, -189.2985436216386], [1487030400000, -177.23897746533885], [1487116800000, -168.81048600172426], [1487203200000, -153.567777106618], [1487289600000, -100.68656755367601], [1487376000000, -75.45062831022642], [1487462400000, -108.96925310011147], [1487548800000, -93.55645410433635], [1487635200000, -64.99901460270985], [1487721600000, -35.97916689891963], [1487808000000, 11.907830891544563], [1487894400000, 79.17337762993907], [1487980800000, 63.83959165222768], [1488067200000, 56.934345820365024], [1488153600000, 39.51527421768219], [1488240000000, 29.178495769746178], [1488326400000, 90.5461984934916], [1488412800000, 125.16602192597361], [1488499200000, 202.8611725980984], [1488585600000, 192.33254826111124], [1488672000000, 169.6391569633472], [1488758400000, 131.66311257969505], [1488844800000, 81.78576161842057], [1488931200000, 32.298695515251666], [1489017600000, 76.40769452094537], [1489104000000, 48.29837418920397], [1489190400000, 126.40156541996384], [1489276800000, 139.65251481260339], [1489363200000, 109.49731764386615], [1489449600000, 93.86578760808288], [1489536000000, 125.14962154414206], [1489622400000, 60.5387613437897], [1489708800000, -14.978391820111028], [1489795200000, -133.83676122325733], [1489881600000, -82.97150756498695], [1489968000000, -93.14539488614082], [1490054400000, -24.631516310702864], [1490140800000, -96.6398988220285], [1490227200000, -115.51895970001124], [1490313600000, -241.49363545392362], [1490400000000, -205.8635780366203], [1490486400000, -210.9811099227586], [1490572800000, -140.35925530197392], [1490659200000, -147.93213803996605], [1490745600000, -152.0784138672675], [1490832000000, -173.71301407104056], [1490918400000, -133.64053482971235], [1491004800000, -124.16591991860082], [1491091200000, -122.02492700563175], [1491177600000, -89.64679276292031], [1491264000000, -107.03866165153454], [1491350400000, -127.07710246152033], [1491436800000, -85.51569066503475], [1491523200000, -84.77840133451764], [1491609600000, -96.730832181104], [1491696000000, -82.75955341642702], [1491782400000, -106.04044872361692], [1491868800000, -108.02778455985322], [1491955200000, -130.72764621885153], [1492041600000, -182.15251448557228], [1492128000000, -169.2489416488304], [1492214400000, -181.08707064848568], [1492300800000, -187.16600917869482], [1492387200000, -188.6870184540319], [1492473600000, -191.5550169482733], [1492560000000, -205.58686820347475], [1492646400000, -212.63032276819717], [1492732800000, -196.2464542226146], [1492819200000, -221.5225034555524], [1492905600000, -220.07281277564448], [1492992000000, -241.8652012565217], [1493078400000, -248.50848211191806], [1493164800000, -258.9009377317607], [1493251200000, -237.6266161715082], [1493337600000, -229.03274385775262], [1493424000000, -230.43370859957827], [1493510400000, -231.40700189687823], [1493596800000, -209.66373087875286], [1493683200000, -201.988123779553], [1493769600000, -207.9542841047271], [1493856000000, -203.44966577413516], [1493942400000, -202.19041167211208], [1494028800000, -187.15533793995746], [1494115200000, -191.63866561330724], [1494201600000, -154.7866781161738], [1494288000000, -153.35279882053283], [1494374400000, -147.3881348175887], [1494460800000, -132.7091697367714], [1494547200000, -189.63216505851233], [1494633600000, -158.8723004468361], [1494720000000, -166.12910951082813], [1494806400000, -196.81597829484258], [1494892800000, -201.13295256699075], [1494979200000, -172.6084537604911], [1495065600000, -147.1034453285506], [1495152000000, -125.79735486466802], [1495238400000, -103.18845554782172], [1495324800000, -107.3788884583571], [1495411200000, -90.72041237048973], [1495497600000, -64.36790304228452], [1495584000000, -14.753461412209958], [1495670400000, -53.22498680189335], [1495756800000, -73.9551628222656], [1495843200000, -128.88773507740655], [1495929600000, -88.38786459221137], [1496016000000, -62.848640000671026], [1496102400000, -102.67333128279665], [1496188800000, -57.000951906521095], [1496275200000, -38.23859174016127], [1496361600000, -22.51386687256479], [1496448000000, -14.793802118455119], [1496534400000, -19.244369534975363], [1496620800000, 22.221247635127042], [1496707200000, 30.826293991724015], [1496793600000, 17.55542259097524], [1496880000000, 34.73804565961234], [1496966400000, 41.87975797660408], [1497052800000, 53.40794295298099], [1497139200000, 67.35997831403404], [1497225600000, 28.944874060470966], [1497312000000, 25.291550130796168], [1497398400000, -18.147830407843912], [1497484800000, -21.191101274785865], [1497571200000, 6.5912742003873745], [1497657600000, 54.07801186155143], [1497744000000, 38.289278778841435], [1497830400000, 41.19254468139479], [1497916800000, 51.179570619729475], [1498003200000, 37.02405827805444], [1498089600000, 21.996512093726892], [1498176000000, 42.10365063843756], [1498262400000, 33.56436354256073], [1498348800000, 29.838365485390227], [1498435200000, -2.9656406539436375], [1498521600000, 23.670733066146], [1498608000000, 21.197989200216625], [1498694400000, -10.712909459455659], [1498780800000, -10.637216436597896], [1498867200000, -10.109789330176227], [1498953600000, 19.4982942028837], [1499040000000, 8.086420117428474], [1499126400000, 24.19406326790613], [1499212800000, 25.977768863906817], [1499299200000, -8.76837216221827], [1499385600000, -18.9839653106568], [1499472000000, -8.152598170529359], [1499558400000, -10.528940533242576], [1499644800000, -73.58388641857312], [1499731200000, -71.01276888355392], [1499817600000, -48.703600803759514], [1499904000000, -93.38454503997241], [1499990400000, -126.2141933106177], [1500076800000, -213.24524676961698], [1500163200000, -232.75615703406334], [1500249600000, -160.143044667906], [1500336000000, -126.67848987254752], [1500422400000, -134.35252858742092], [1500508800000, -41.00204232885028], [1500595200000, -78.84165173278802], [1500681600000, -68.57253583143108], [1500768000000, -82.7976108619822], [1500854400000, -93.66845588958756], [1500940800000, -117.3578943251872], [1501027200000, -122.81291120566482], [1501113600000, -107.15349907165057], [1501200000000, -95.2244227422292], [1501286400000, -122.94660039877203], [1501372800000, -119.05574666150744], [1501459200000, -110.5899350826121], [1501545600000, -132.82268166882477], [1501632000000, -139.10566789275015], [1501718400000, -130.782254431174], [1501804800000, -126.46340831419593], [1501891200000, -79.97601529450526], [1501977600000, -85.82473392640554], [1502064000000, -66.94484160383684], [1502150400000, -68.17982450450302], [1502236800000, -83.43379407564635], [1502323200000, -79.1592471153042], [1502409600000, -53.896748729790374], [1502496000000, -32.5141151446735], [1502582400000, -16.17010406522263], [1502668800000, 7.082141166664655], [1502755200000, -9.157575236929915], [1502841600000, 6.570940626970469], [1502928000000, 9.199418788525804], [1503014400000, -11.96183058790325], [1503100800000, -4.117287642872384], [1503187200000, -8.671695294385813], [1503273600000, -15.991486261329896], [1503360000000, -10.749737148837085], [1503446400000, -4.383593811964602], [1503532800000, 24.54939033403116], [1503619200000, 18.618173132437278], [1503705600000, 18.562066426217143], [1503792000000, 21.71289461114543], [1503878400000, 16.80336103023228], [1503964800000, 31.597155341293956], [1504051200000, 27.901623792037867], [1504137600000, 55.7796846002239], [1504224000000, 58.92722177153803], [1504310400000, 34.423338830061084], [1504396800000, 40.00064131371056], [1504483200000, 7.217634423783011], [1504569600000, 22.35691761931912], [1504656000000, 35.739556351837734], [1504742400000, 55.07526915133269], [1504828800000, 26.096956678653896], [1504915200000, 19.08302621231155], [1505001600000, 13.092298812729837], [1505088000000, -3.9265159281704882], [1505174400000, -2.0918259355748887], [1505260800000, -27.066341652964297], [1505347200000, -87.10568013001057], [1505433600000, -44.13598856290014], [1505520000000, -54.87451936788284], [1505606400000, -55.08807216881985], [1505692800000, -31.932134025997016], [1505779200000, -42.04489888466355], [1505865600000, -48.642177707266], [1505952000000, -79.4568299154131], [1506038400000, -85.69825063840153], [1506124800000, -75.58508577067369], [1506211200000, -87.28659361139921], [1506297600000, -68.25961155223968], [1506384000000, -64.89482044534486], [1506470400000, -43.54889704444321], [1506556800000, -55.33468664544182], [1506643200000, -60.95953391191699], [1506729600000, -51.45891395542378], [1506816000000, -53.448164530728036], [1506902400000, -55.517800037531515], [1506988800000, -58.11181451412568], [1507075200000, -68.59836456939342], [1507161600000, -72.95005751870451], [1507248000000, -73.96173266104273], [1507334400000, -72.74929607782224], [1507420800000, -65.06316526268381], [1507507200000, -53.81155671032349], [1507593600000, -52.85705137033983], [1507680000000, -55.363441605738444], [1507766400000, -31.13585909634122], [1507852800000, -22.158159238248913], [1507939200000, -14.969229460646261], [1508025600000, -19.528347891784847], [1508112000000, -18.633029161705963], [1508198400000, -24.626126708992217], [1508284800000, -35.32658040273367], [1508371200000, -35.09537691728019], [1508457600000, -20.679931558968974], [1508544000000, -19.900783930687282], [1508630400000, -21.874885810581873], [1508716800000, -27.576812818027292], [1508803200000, -44.45680149435276], [1508889600000, -44.858331569736606], [1508976000000, -41.56947242094594], [1509062400000, -43.09297571927863], [1509148800000, -46.61484381799971], [1509235200000, -32.63513266986695], [1509321600000, -37.95907358540808], [1509408000000, -29.671866882210168], [1509494400000, -28.43364200536797], [1509580800000, -21.9815796804225], [1509667200000, -18.129958332449462], [1509753600000, -14.679875012980744], [1509840000000, -14.543956029150365], [1509926400000, -32.0115075747982], [1510012800000, -29.156336174432965], [1510099200000, -29.9430025987121], [1510185600000, -42.828406555030085], [1510272000000, -58.34093157710225], [1510358400000, -65.8566993601114], [1510444800000, -84.34446585808604], [1510531200000, -69.95530422193332], [1510617600000, -68.29949691142969], [1510704000000, -55.170507720187175], [1510790400000, -47.1037401398016], [1510876800000, -53.5520459750266], [1510963200000, -54.355977690022485], [1511049600000, -52.37503406221933], [1511136000000, -52.85052715770877], [1511222400000, -55.049328489673115], [1511308800000, -54.37854999849145], [1511395200000, -61.663646283755895], [1511481600000, -58.446617440709076], [1511568000000, -50.787613838237746], [1511654400000, -42.80766196914615], [1511740800000, -40.28042814964357], [1511827200000, -39.94798225816149], [1511913600000, -42.19951355634598], [1512000000000, -42.715792793043704], [1512086400000, -30.602968781254106], [1512172800000, -28.225204649867777], [1512259200000, -26.467473351187834], [1512345600000, -24.419770419448582], [1512432000000, -27.58654959362508], [1512518400000, -10.899563853569987], [1512604800000, 6.505012343624458], [1512691200000, 2.639329320673795], [1512777600000, -2.9582028690279287], [1512864000000, -1.9607072370071421], [1512950400000, 7.784876831755383], [1513036800000, 6.6914379276535385], [1513123200000, 3.740814286441207], [1513209600000, 9.064235324672893], [1513296000000, 13.413532481887955], [1513382400000, 20.38427054226159], [1513468800000, 20.07447838212161], [1513555200000, 21.82850415038378], [1513641600000, 17.45122769397014], [1513728000000, 12.7785847619258], [1513814400000, 12.66303848775155], [1513900800000, -1.4994823688647045], [1513987200000, 2.476609189767231], [1514073600000, 1.0508181860292325], [1514160000000, 5.121423026885424], [1514246400000, 18.321982298076506], [1514332800000, 14.547561275052402], [1514419200000, 12.119445810781656], [1514505600000, 8.665526819213937], [1514592000000, -7.260740387012163], [1514678400000, 5.086497435485882], [1514764800000, 6.9261739143859415], [1514851200000, 22.32005834806813], [1514937600000, 22.40764878649611], [1515024000000, 28.82552716611417], [1515110400000, 36.17971740329864], [1515196800000, 31.855185092152993], [1515283200000, 34.50560945524603], [1515369600000, 37.90360166192107], [1515456000000, 38.23440190536567], [1515542400000, 39.78834207122435], [1515628800000, 31.367604383153235], [1515715200000, 33.20999196772647], [1515801600000, 31.447815842142973], [1515888000000, 35.53182569697492], [1515974400000, 41.50245494546974], [1516060800000, 23.96119207093517], [1516147200000, 18.41104265842955], [1516233600000, 17.811951575202187], [1516320000000, 19.755427381229197], [1516406400000, 25.65302161360728], [1516492800000, 22.996142090582083], [1516579200000, 18.661231522579413], [1516665600000, 19.044344301775652], [1516752000000, 23.082981016346878], [1516838400000, 21.28227741694684], [1516924800000, 18.36583630021792], [1517011200000, 19.794700913442], [1517097600000, 30.32068522893337], [1517184000000, 24.877370005277697], [1517270400000, 9.870825143310043], [1517356800000, 10.968317646928796], [1517443200000, -7.210203616208787], [1517529600000, -14.067761194558614], [1517616000000, -10.147645451815862], [1517702400000, -21.85849729187231], [1517788800000, -54.80570898712267], [1517875200000, -36.20466406271834], [1517961600000, -36.92854666828515], [1518048000000, -24.19082015193274], [1518134400000, -18.64530588152482], [1518220800000, -20.90473207762693], [1518307200000, -29.604825927926555], [1518393600000, -18.912265656936654], [1518480000000, -23.731428643314985], [1518566400000, -2.044102746565443], [1518652800000, 6.512164628912984], [1518739200000, 7.195593607814345], [1518825600000, 20.207093397945556], [1518912000000, 9.624318421227628], [1518998400000, 14.910216867037548], [1519084800000, 15.35959075664988], [1519171200000, 14.301728724708028], [1519257600000, 8.106614379041588], [1519344000000, 10.970551841994421], [1519430400000, 9.367012074611779], [1519516800000, 4.370809607926219], [1519603200000, 13.813628795389747], [1519689600000, 18.660475501904244], [1519776000000, 21.034970746843868], [1519862400000, 33.798429804189766], [1519948800000, 35.751137489140206], [1520035200000, 43.86324590960993], [1520121600000, 41.12428308035231], [1520208000000, 40.1555020571206], [1520294400000, 31.968139937267722], [1520380800000, 29.70806217238001], [1520467200000, 27.069158774365746], [1520553600000, 27.86490913972625], [1520640000000, 22.335975465258628], [1520726400000, 31.266344789207352], [1520812800000, 25.78646249534799], [1520899200000, 24.00560010137758], [1520985600000, 11.82302622115202], [1521072000000, 12.920706926112757], [1521158400000, 15.011515136488867], [1521244800000, 6.558687698935273], [1521331200000, 11.105136572622484], [1521417600000, 20.46012083174344], [1521504000000, 24.700621176987568], [1521590400000, 25.55097860309769], [1521676800000, 21.874045199991656], [1521763200000, 25.340215134597088], [1521849600000, 16.43651418900447], [1521936000000, 14.008929660490708], [1522022400000, 9.552304944744094], [1522108800000, -0.6932641388373213], [1522195200000, 6.413189092996561], [1522281600000, -17.60388726479664], [1522368000000, -23.50028233860735], [1522454400000, -25.285949089198255], [1522540800000, -29.968295088746856], [1522627200000, -21.471747820674295], [1522713600000, -15.098472546780272], [1522800000000, -28.868489843243992], [1522886400000, -37.96517670551253], [1522972800000, -42.71810409872734], [1523059200000, -38.27885251141049], [1523145600000, -35.82904877785808], [1523232000000, -39.97492962359979], [1523318400000, -38.34607298439272], [1523404800000, -35.31877932979444], [1523491200000, -18.114431637823714], [1523577600000, -17.245282391412957], [1523664000000, -17.343496463468227], [1523750400000, -11.314854387996832], [1523836800000, -15.37274226778186], [1523923200000, -18.54984971341321], [1524009600000, -11.573257068423288], [1524096000000, -10.591281983018632], [1524182400000, 1.2551461384418872], [1524268800000, -0.02479541440760613], [1524355200000, -3.260783398937008], [1524441600000, 0.8087752335042637], [1524528000000, 13.701935558721033], [1524614400000, 5.1412558947928915], [1524700800000, 10.959460367484894], [1524787200000, 8.43672399362356], [1524873600000, 14.03489091335021], [1524960000000, 13.306548368075823], [1525046400000, 13.986604435045422], [1525132800000, 12.902505072278302], [1525219200000, 17.915468748364077], [1525305600000, 25.657805724385668], [1525392000000, 27.06098687449432], [1525478400000, 28.618073635532653], [1525564800000, 23.75026867925297], [1525651200000, 23.356788483890284], [1525737600000, 20.955926460897018], [1525824000000, 25.78065652308848], [1525910400000, 21.85308631205021], [1525996800000, 12.617773107236417], [1526083200000, 14.305155318829406], [1526169600000, 20.378693038528695], [1526256000000, 21.98426853245587], [1526342400000, 20.34219096389785], [1526428800000, 22.453597907612163], [1526515200000, 14.349739489140802], [1526601600000, 19.83600635377229], [1526688000000, 19.760324230967456], [1526774400000, 28.471407955541963], [1526860800000, 26.66310427397741], [1526947200000, 18.750814093639974], [1527033600000, 11.272031255309628], [1527120000000, 10.089934370852461], [1527206400000, 14.478569107495048], [1527292800000, 10.35059682318672], [1527379200000, 14.684590053203692], [1527465600000, 7.253945764304035], [1527552000000, 17.538695378443947], [1527638400000, 16.856738364501723], [1527724800000, 19.061220580061956], [1527811200000, 23.766233570811323], [1527897600000, 23.649580482853196], [1527984000000, 30.02295350178082], [1528070400000, 20.662236248677402], [1528156800000, 27.13512195678402], [1528243200000, 28.410196146596206], [1528329600000, 29.654954019689228], [1528416000000, 31.558692736085277], [1528502400000, 25.332338242736284], [1528588800000, 9.647471008290267], [1528675200000, 8.331765941745516], [1528761600000, 4.230986301560279], [1528848000000, -4.3143328950592945], [1528934400000, 8.602537227797427], [1529020800000, 3.766135411375899], [1529107200000, 3.211083377201703], [1529193600000, 1.9994039447551586], [1529280000000, 3.8798336794295665], [1529366400000, 5.618603001985207], [1529452800000, 4.250231188287955], [1529539200000, 6.266818316702086], [1529625600000, -14.789122524864183], [1529712000000, -14.23154038946592], [1529798400000, -14.498798007413598], [1529884800000, -17.216069222843032], [1529971200000, -25.6372747512018], [1530057600000, -24.521281297110647], [1530144000000, -31.214498427783553], [1530230400000, -21.327995534501554], [1530316800000, -17.93357937695606], [1530403200000, -19.520708208840915], [1530489600000, -15.64486644581251], [1530576000000, -20.416840413145337], [1530662400000, -17.63288509222616], [1530748800000, -17.210277619207318], [1530835200000, -14.938079670174204], [1530921600000, -9.580356712271396], [1531008000000, -11.601053354138799], [1531094400000, -15.97742068895269], [1531180800000, -28.914456325576452], [1531267200000, -22.18921923480508], [1531353600000, -27.15391084132932], [1531440000000, -24.766768559874833], [1531526400000, -22.66438890134316], [1531612800000, -20.54497477455635], [1531699200000, -10.894594458841595], [1531785600000, 3.5848646808419176], [1531872000000, 8.770323392959199], [1531958400000, 9.941763229635683], [1532044800000, 7.425496555433995], [1532131200000, 11.53529730081624], [1532217600000, 10.060140738335122], [1532304000000, 19.30097704559398], [1532390400000, 33.60556543352112], [1532476800000, 33.73038907469288], [1532563200000, 26.587593705158895], [1532649600000, 31.40092676047152], [1532736000000, 34.764019024421316], [1532822400000, 33.314804167461205], [1532908800000, 34.04982429494203], [1532995200000, 25.288365798225243], [1533081600000, 26.38361051752571], [1533168000000, 21.964290130990435], [1533254400000, 19.062108950248557], [1533340800000, 9.571959311155354], [1533427200000, 8.540118376617556], [1533513600000, 7.3030339295825115], [1533600000000, -0.8311160302766893], [1533686400000, -8.340548024582574], [1533772800000, -1.1181655659961507], [1533859200000, -14.655729583378331], [1533945600000, -10.456433249121005], [1534032000000, -9.494889604991727], [1534118400000, -11.17641062388958], [1534204800000, -15.977025935622692], [1534291200000, -9.10987793518359], [1534377600000, -8.390928888265648], [1534464000000, -1.542856628356958], [1534550400000, -6.566577481553679], [1534636800000, -4.4848692503414895], [1534723200000, -10.918667603134622], [1534809600000, -6.6414870173176155], [1534896000000, -6.69541530899528], [1534982400000, -2.1874210380913155], [1535068800000, 1.182860680603028], [1535155200000, 2.7837361101601346], [1535241600000, 1.374600203852765], [1535328000000, 8.298064377931041], [1535414400000, 12.462206154946273], [1535500800000, 14.581557063043704], [1535587200000, 11.281156122452387], [1535673600000, 11.349538347694136], [1535760000000, 17.137197578610028], [1535846400000, 19.00252335328429], [1535932800000, 20.444440091512035], [1536019200000, 23.632406037810085], [1536105600000, 7.551508651819461], [1536192000000, -1.333904671930327], [1536278400000, -5.838642327801381], [1536364800000, -11.425109663408307], [1536451200000, -9.957493690629462], [1536537600000, -5.420288046210146], [1536624000000, -5.296974393540097], [1536710400000, -4.082296727086714], [1536796800000, 0.04365420579523516], [1536883200000, -2.1202059396960635], [1536969600000, -0.4832693425138359], [1537056000000, -1.208431355094433], [1537142400000, -9.682768338899791], [1537228800000, -5.460066738179762], [1537315200000, -3.5338998749851953], [1537401600000, 0.5388807468215191], [1537488000000, 7.037671167548524], [1537574400000, 6.110753750546394], [1537660800000, 5.342954845056852], [1537747200000, -0.027560039719560336], [1537833600000, -3.115559723776812], [1537920000000, -1.8542430181792042], [1538006400000, 6.786715788708591], [1538092800000, 4.98736385827408], [1538179200000, 4.084664359376063], [1538265600000, 4.3234881012475626], [1538352000000, 2.2152362963535666], [1538438400000, 0.7950292443746321], [1538524800000, 0.0026464784960467114], [1538611200000, 5.366758726566275], [1538697600000, 6.5356750696715835], [1538784000000, 5.180789945974595], [1538870400000, 4.633090381565296], [1538956800000, 5.112033748448766], [1539043200000, 4.635897801863052], [1539129600000, 2.7355121529632243], [1539216000000, -6.750064254966446], [1539302400000, -4.971591072994556], [1539388800000, -4.72480480083351], [1539475200000, -5.269518476620249], [1539561600000, 5.743802138541412], [1539648000000, 5.031996350996508], [1539734400000, 8.903265943543943], [1539820800000, 7.813000298310953], [1539907200000, 8.258382745899667], [1539993600000, 8.911638785065804], [1540080000000, 8.292322010829594], [1540166400000, 17.704823268655446], [1540252800000, 22.268778105314993], [1540339200000, 24.443230936293162], [1540425600000, 29.145836313410484], [1540512000000, 29.5839002260588], [1540598400000, 38.49983518322591], [1540684800000, 34.58095140880363], [1540771200000, 43.36705627785716], [1540857600000, 47.35170883351617], [1540944000000, 42.796526444420635], [1541030400000, 48.878966269580985], [1541116800000, 54.571919011251225], [1541203200000, 59.27874224366519], [1541289600000, 59.391065828069486], [1541376000000, 76.31938450735998], [1541462400000, 80.57915839569978], [1541548800000, 80.86516327113048], [1541635200000, 88.56137423723328], [1541721600000, 93.05652077698954], [1541808000000, 97.94463794649312], [1541894400000, 92.89682319615457], [1541980800000, 112.48043895188897], [1542067200000, 115.80753009851941], [1542153600000, 89.09106808310241], [1542240000000, 99.40874085248271], [1542326400000, 104.88952554870292], [1542412800000, 108.54099627292226], [1542499200000, 104.66599130275375], [1542585600000, 75.03567450278064], [1542672000000, 50.99285559056932], [1542758400000, 53.37493388656986], [1542844800000, 39.84919250063206], [1542931200000, 53.55650515547484], [1543017600000, 13.18275953774446], [1543104000000, 22.24091002691671], [1543190400000, 4.776334877084423], [1543276800000, 8.87497527140988], [1543363200000, 41.298310044218965], [1543449600000, 49.51755243553862], [1543536000000, 32.65098271885461], [1543622400000, 44.79755330228761], [1543708800000, 36.326934976512916], [1543795200000, 14.043957942388374], [1543881600000, 19.70859538218474], [1543968000000, -0.9825756200842761], [1544054400000, -19.686579472295534], [1544140800000, -26.55352156897527], [1544227200000, -21.957713192735696], [1544313600000, -16.15649242984034], [1544400000000, -32.50774264774816], [1544486400000, -40.52489898283818], [1544572800000, -34.671778606231555], [1544659200000, -46.26019031227759], [1544745600000, -56.275439397243986], [1544832000000, -55.91679687654391], [1544918400000, -56.676098307665825], [1545004800000, -28.341461694258214], [1545091200000, -9.869617299552942], [1545177600000, -10.570912339605115], [1545264000000, 32.241610636017526], [1545350400000, 9.233693893227269], [1545436800000, 21.53246651893187], [1545523200000, 18.44234956125422], [1545609600000, 24.07067486042274], [1545696000000, 4.560846290127188], [1545782400000, 4.184264665153933], [1545868800000, -4.16974900408286], [1545955200000, 20.31124776096385], [1546041600000, 7.180663241065531], [1546128000000, 17.090713070075594], [1546214400000, 5.458341805485361], [1546300800000, 18.07698167049091], [1546387200000, 22.978280831133475], [1546473600000, 20.1901778579263], [1546560000000, 23.602304544783124], [1546646400000, 19.12575470288516], [1546732800000, 45.211920862854754], [1546819200000, 41.206881046532885], [1546905600000, 42.08466355348389], [1546992000000, 42.900838565849995], [1547078400000, 13.285877026945286], [1547164800000, 7.232991424670672], [1547251200000, 3.8451957884979038], [1547337600000, -1.244592999259794], [1547424000000, 16.64735130081931], [1547510400000, 9.214618943808773], [1547596800000, 12.228797323830008], [1547683200000, 16.842580861144484], [1547769600000, 6.612767176784928], [1547856000000, 11.742438056917877], [1547942400000, -2.0126881572288084], [1548028800000, -1.8235995004657752], [1548115200000, 0.972601403337535], [1548201600000, -2.2616409418428702], [1548288000000, 2.4548044474532844], [1548374400000, -7.183851965915096], [1548460800000, -10.319461166091514], [1548547200000, -6.666174675271918], [1548633600000, -21.34988751259766], [1548720000000, -24.984454225455806], [1548806400000, -19.8563877124584], [1548892800000, -21.35449744824939], [1548979200000, -26.435030765740635], [1549065600000, -25.442483248391795], [1549152000000, -25.382604428591094], [1549238400000, -30.235772718363137], [1549324800000, -31.292131307943464], [1549411200000, -37.40561507415998], [1549497600000, -38.30862663747473], [1549584000000, -12.657228048409706], [1549670400000, -18.452742433823573], [1549756800000, -8.9425409222398], [1549843200000, -18.941519443188554], [1549929600000, -21.18661915939697], [1550016000000, -23.195926770424308], [1550102400000, -24.09833254457078], [1550188800000, -25.265329675736893], [1550275200000, -29.583299762108254], [1550361600000, -16.554951021673446], [1550448000000, 4.158904664957618], [1550534400000, 1.8400220196249393], [1550620800000, 4.862668387112308], [1550707200000, 3.145073216826745], [1550793600000, 5.741754748206745], [1550880000000, 13.601739877384148], [1550966400000, -12.438958377918198], [1551052800000, -2.4691763707432983], [1551139200000, -8.69386927686412], [1551225600000, -9.95040684838716], [1551312000000, -9.502397842644541], [1551398400000, -10.815022134687752], [1551484800000, -13.465165342863997], [1551571200000, -14.691480011242675], [1551657600000, -19.412299697997355], [1551744000000, -19.929753562055453], [1551830400000, -22.938581744463704], [1551916800000, -20.44199529075729], [1552003200000, -25.33805115928851], [1552089600000, -21.494504780138072], [1552176000000, -23.54762308443867], [1552262400000, -27.875375791975898], [1552348800000, -37.48270597040687], [1552435200000, -42.736325754388304], [1552521600000, -37.64639776384922], [1552608000000, -37.49265814579417], [1552694400000, -30.56162795006685], [1552780800000, -34.80736661217827], [1552867200000, -34.39456749705221], [1552953600000, -43.80766970179843], [1553040000000, -45.66601910438294], [1553126400000, -46.66084334744505], [1553212800000, -49.65675162897651], [1553299200000, -49.73033835032072], [1553385600000, -52.87308961172528], [1553472000000, -59.0695674190257], [1553558400000, -70.75768910829345], [1553644800000, -64.76147683606723], [1553731200000, -59.375340779022395], [1553817600000, -56.92449682844091], [1553904000000, -56.8335747799415], [1553990400000, -59.944865106209534], [1554076800000, -57.430762029791424], [1554163200000, -18.290628114556398], [1554249600000, -16.060838061500135], [1554336000000, -14.797045500306524], [1554422400000, -12.074013380431438], [1554508800000, -12.618805115817736], [1554595200000, -7.109867969382492], [1554681600000, -1.9507962204364162], [1554768000000, -10.902750710284238], [1554854400000, -7.334093410505091], [1554940800000, -18.89234931633257], [1555027200000, -21.89382148818936], [1555113600000, -28.17205370068865], [1555200000000, -23.078246829840907], [1555286400000, -33.25604695231891], [1555372800000, -29.531081568446382], [1555459200000, -30.498225745093976], [1555545600000, -26.340898542419836], [1555632000000, -28.035928242780926], [1555718400000, -32.14739790682415], [1555804800000, -36.287420029232464], [1555891200000, -35.47823058824821], [1555977600000, -32.26511996231818], [1556064000000, -36.71721133808899], [1556150400000, -50.86755968193319], [1556236800000, -49.54928087807781], [1556323200000, -55.431539739186974], [1556409600000, -59.226835347694646], [1556496000000, -64.00423415882307], [1556582400000, -60.321389096946916], [1556668800000, -59.413344513342395], [1556755200000, -54.70420277761605], [1556841600000, -46.06755834962348], [1556928000000, -48.06921854823389], [1557014400000, -56.306227404277195], [1557100800000, -59.104647034201776], [1557187200000, -54.960590606571145], [1557273600000, -48.7769303121828], [1557360000000, -41.730951146633345], [1557446400000, -36.346908362704994], [1557532800000, -14.825526269959823], [1557619200000, -26.246062666801606], [1557705600000, -7.367537600312005], [1557792000000, -1.1998449675098755], [1557878400000, 2.426604944436747], [1557964800000, -3.074040330549394], [1558051200000, -17.416605255324953], [1558137600000, -20.273008272668676], [1558224000000, -4.877228776363211], [1558310400000, -8.982147627974996], [1558396800000, -6.2970984984094684], [1558483200000, -14.543181276005896], [1558569600000, -9.38140754083372], [1558656000000, -13.056397225147862], [1558742400000, -13.480343168210311], [1558828800000, -2.7670806058887933], [1558915200000, -2.7807450809023635], [1559001600000, -1.991880623163297], [1559088000000, -7.4061771939400955], [1559174400000, -11.291016161859659], [1559260800000, -14.086840493366537], [1559347200000, -14.605808401056947], [1559433600000, -8.793707725078207], [1559520000000, -21.8777761117899], [1559606400000, -30.803810381793085], [1559692800000, -35.173846781121426], [1559779200000, -30.68118507311374], [1559865600000, -33.06123040690562], [1559952000000, -35.814126999879846], [1560038400000, -40.181700203109585], [1560124800000, -35.98487879087497], [1560211200000, -39.69716470530173], [1560297600000, -39.66835500181881], [1560384000000, -32.58530998563202], [1560470400000, -30.334641150732836], [1560556800000, -27.932960128665627], [1560643200000, -21.653403837269508], [1560729600000, -20.095628366284387], [1560816000000, -22.230658842562065], [1560902400000, -24.231366288101867], [1560988800000, -16.661146583023566], [1561075200000, -11.44392807544611], [1561161600000, -5.808989403650855], [1561248000000, 1.1508356286201433], [1561334400000, 0.6572967142712116], [1561420800000, 11.115638329944517], [1561507200000, 17.76420316136253], [1561593600000, 4.129137782586156], [1561680000000, 13.926878580873165], [1561766400000, 11.13698565074958], [1561852800000, 3.759768634203823], [1561939200000, -0.6114094927000338], [1562025600000, 6.472477404632713], [1562112000000, 15.34114056753819], [1562198400000, 5.999229512706819], [1562284800000, 3.554718130408304], [1562371200000, 6.6874470402448765], [1562457600000, 11.449900707583339], [1562544000000, 15.396183795525417], [1562630400000, 23.197494146274977], [1562716800000, 16.52048898655994], [1562803200000, 6.34172182468302], [1562889600000, 10.542265228449338], [1562976000000, 7.879352461698971], [1563062400000, -4.294927215458159], [1563148800000, 1.6898827779376404], [1563235200000, -11.377333945044683], [1563321600000, -8.015412962412825], [1563408000000, 0.4928581626029995], [1563494400000, -0.6996963167408126], [1563580800000, 3.6036633525614263], [1563667200000, 0.4573432110932174], [1563753600000, -5.2093254762922925], [1563840000000, -8.527597545162592], [1563926400000, -8.137072552966913], [1564012800000, -8.409733946090626], [1564099200000, -9.87442810268928], [1564185600000, -12.842195317707763], [1564272000000, -13.3724270640256], [1564358400000, -17.300333088007392], [1564444800000, -13.378401195552442], [1564531200000, -3.3667107586701093], [1564617600000, 0.14914640898990683], [1564704000000, 0.3620067010720902], [1564790400000, 5.499140278843413], [1564876800000, 5.766292471983775], [1564963200000, 9.58852061305933], [1565049600000, 8.158617059706813], [1565136000000, 17.71729543362372], [1565222400000, 17.885087953455184], [1565308800000, 16.30975444047212], [1565395200000, 11.893991974952883], [1565481600000, 13.628573370857168], [1565568000000, 8.617374317115775], [1565654400000, 4.665556906789334], [1565740800000, -1.2440141162277598], [1565827200000, 1.9833135790745473], [1565913600000, 2.207663080111871], [1566000000000, 0.8178956392161751], [1566086400000, 1.8785655451754906], [1566172800000, 5.983501936298296], [1566259200000, 5.1685149173735], [1566345600000, -0.20409927212870116], [1566432000000, -0.7617471127993269], [1566518400000, 3.376166213555365], [1566604800000, 0.49306627906091194], [1566691200000, 0.14932254961797753], [1566777600000, 2.2424448426672257], [1566864000000, 4.3234600504019625], [1566950400000, -0.5105033287754566], [1567036800000, -2.772333638339603], [1567123200000, -1.0397360327061733], [1567209600000, -0.6043289429836136], [1567296000000, 2.0289900346743366], [1567382400000, 9.38040062236044], [1567468800000, 16.569264270078634], [1567555200000, 16.217610995391595], [1567641600000, 17.05001872527012], [1567728000000, 14.672734145282249], [1567814400000, 17.042655918856923], [1567900800000, 18.342829642188434], [1567987200000, 15.722005271916657], [1568073600000, 17.705207674218656], [1568160000000, 16.899889087675035], [1568246400000, 21.59517170879272], [1568332800000, 22.352135985627825], [1568419200000, 22.53647897997746], [1568505600000, 23.96237479722805], [1568592000000, 21.635895226356183], [1568678400000, 25.68044830978343], [1568764800000, 24.463193551590933], [1568851200000, 27.612331208847763], [1568937600000, 28.024137181503903], [1569024000000, 25.618413178963237], [1569110400000, 27.11010105209965], [1569196800000, 20.2770988554027], [1569283200000, 5.958135145458641], [1569369600000, 5.882422304350428], [1569456000000, 0.08413842052829068], [1569542400000, -1.0745661010585081], [1569628800000, -2.9836324032652897], [1569715200000, -6.4279723327318266], [1569801600000, -2.8024637287416], [1569888000000, -1.5779068135268517], [1569974400000, 2.0765991478920114], [1570060800000, -0.4262170106915164], [1570147200000, -5.796674453076889], [1570233600000, -8.161548960939172], [1570320000000, -15.354885350637346], [1570406400000, -8.956129805774253], [1570492800000, -8.106952822204562], [1570579200000, 2.592888934139239], [1570665600000, 3.0318098295427376], [1570752000000, -5.882582339832993], [1570838400000, -7.703162786030077], [1570924800000, -10.687900600355874], [1571011200000, -7.893113601916866], [1571097600000, -10.981798793349014], [1571184000000, -10.17044034685324], [1571270400000, -7.769055917055482], [1571356800000, -13.312881353479384], [1571443200000, -15.876515515940298], [1571529600000, -12.609310274215602], [1571616000000, -10.103157223790731], [1571702400000, -13.850048458129606], [1571788800000, -23.341187994351287], [1571875200000, -20.915158185960138], [1571961600000, 4.567172256381411], [1572048000000, 12.253469138564839], [1572134400000, 17.787922343580334], [1572220800000, 14.135125215913405], [1572307200000, 16.971856810467983], [1572393600000, 11.803865471031457], [1572480000000, 15.205458164139316], [1572566400000, 18.961161287641943], [1572652800000, 20.05252432222761], [1572739200000, 21.057630476577913], [1572825600000, 25.52326453445025], [1572912000000, 24.01429699997692], [1572998400000, 23.30834398591267], [1573084800000, 23.49177734230682], [1573171200000, 17.312465435904357], [1573257600000, 18.86593088863691], [1573344000000, 24.981629331143267], [1573430400000, 21.96635856453537], [1573516800000, 24.029116860520446], [1573603200000, 22.363743980211098], [1573689600000, 21.941591594097588], [1573776000000, 18.25219111170577], [1573862400000, 20.685105702782323], [1573948800000, 23.607310691478858], [1574035200000, 19.920027664110876], [1574121600000, 21.076605901884136], [1574208000000, 15.242601471824173], [1574294400000, 6.864996003313081], [1574380800000, -3.157900811635386], [1574467200000, 0.2976846224980818], [1574553600000, -10.509768414570885], [1574640000000, -1.7968546086251536], [1574726400000, 1.5859656246155396], [1574812800000, 6.384942795645202], [1574899200000, 4.274577352031258], [1574985600000, 9.15193272483333], [1575072000000, 6.432929274557296], [1575158400000, 0.5625510083465883], [1575244800000, 2.691215512638223], [1575331200000, 5.441740557389835], [1575417600000, -0.3705824985437971], [1575504000000, 5.989067701348915], [1575590400000, 6.15966581496167], [1575676800000, 6.101145708432341], [1575763200000, 3.9416141275356154], [1575849600000, 1.249967714265722], [1575936000000, -0.8022786823715933], [1576022400000, -4.403278960562773], [1576108800000, -1.6359566413066773], [1576195200000, -4.543530474736372], [1576281600000, -8.062798518547368], [1576368000000, -9.930698864577948], [1576454400000, -15.241471140701663], [1576540800000, -25.84883528233786], [1576627200000, -9.388592552329044], [1576713600000, -9.713584691084918], [1576800000000, -13.41063588861499], [1576886400000, -14.15039735670183], [1576972800000, -6.878221535496948], [1577059200000, -11.416559462805708], [1577145600000, -17.57757249877119], [1577232000000, -18.138520027794414], [1577318400000, -14.283209208397182], [1577404800000, -17.83612092938762], [1577491200000, -15.55613578518205], [1577577600000, -14.748743020174686], [1577664000000, -20.844755890509532], [1577750400000, -28.679327588400668], [1577836800000, -27.444214439263874], [1577923200000, -30.822134590480573], [1578009600000, -24.374227480606578], [1578096000000, -23.110748365689005], [1578182400000, -23.84120391142858], [1578268800000, -16.1151421501379], [1578355200000, -13.417128253950466], [1578441600000, -16.270712403306618], [1578528000000, -20.149455027252145], [1578614400000, -13.897739660786499], [1578700800000, -16.902249332404608], [1578787200000, -14.99273686328803], [1578873600000, -16.13209392729175], [1578960000000, -7.463473778412435], [1579046400000, -8.655257074088354], [1579132800000, -9.809240184217458], [1579219200000, -7.351867954352798], [1579305600000, -5.922059088685472], [1579392000000, -10.64860803494605], [1579478400000, -11.134870741505068], [1579564800000, -13.614055874320059], [1579651200000, -14.080360259436844], [1579737600000, -19.24537896969133], [1579824000000, -18.89787758108622], [1579910400000, -19.3506474992501], [1579996800000, -16.7910023705482], [1580083200000, -9.728825273738238], [1580169600000, -4.007162787303059], [1580256000000, -3.507620967130663], [1580342400000, -0.95923556013949], [1580428800000, -3.4149931786340346], [1580515200000, -1.1023083635309092], [1580601600000, -3.4879680668382207], [1580688000000, -3.024941523140427], [1580774400000, -5.4903828081962445], [1580860800000, 3.5353057174802984], [1580947200000, 4.406624379760103], [1581033600000, 4.504566160930011], [1581120000000, 8.498331667293314], [1581206400000, 13.868893356812436], [1581292800000, 11.139829267962341], [1581379200000, 16.31930563406587], [1581465600000, 20.444355704596347], [1581552000000, 40.267966409600206], [1581638400000, 34.02953389138966], [1581724800000, 35.028086138144346], [1581811200000, 35.910916951006726], [1581897600000, 36.61268372981283], [1581984000000, 40.980473873433056], [1582070400000, 34.98119616855482], [1582156800000, 49.523327553062046], [1582243200000, 43.1192677236408], [1582329600000, 48.89123608984448], [1582416000000, 57.01747139050843], [1582502400000, 50.5943205055932], [1582588800000, 42.10070431547476], [1582675200000, 34.21746329642019], [1582761600000, 48.7939826017066], [1582848000000, 41.88132138188524], [1582934400000, 45.56292282502727], [1583020800000, 53.01545200159137], [1583107200000, 53.32799286105143], [1583193600000, 46.30472899218745], [1583280000000, 44.29517021939637], [1583366400000, 62.99696974623248], [1583452800000, 59.47108543720174], [1583539200000, 60.4932079358951], [1583625600000, 51.52128603291817], [1583712000000, 40.44718271013204], [1583798400000, 35.340297809652554], [1583884800000, 33.47302440210831], [1583971200000, -63.170331549804985], [1584057600000, -28.348069761676186], [1584144000000, -45.96851400444899], [1584230400000, -32.472307857521685], [1584316800000, -57.771302001643676], [1584403200000, -46.47326512733832], [1584489600000, -43.945556330652835], [1584576000000, -21.309350964739338], [1584662400000, -14.944773716699729], [1584748800000, -16.499708302064732], [1584835200000, -24.14621744189384], [1584921600000, -8.863402410354865], [1585008000000, -1.52777759441409], [1585094400000, -5.960746884757043], [1585180800000, -9.701776440711512], [1585267200000, -16.582061870709197], [1585353600000, -22.689389506605437], [1585440000000, -33.873518091009885], [1585526400000, -19.605818365104028], [1585612800000, -18.318116901402732], [1585699200000, -17.161906442069494], [1585785600000, -17.50289814322616], [1585872000000, -17.00998620152916], [1585958400000, -15.816407584448541], [1586044800000, -18.06823000879598], [1586131200000, -3.3012817957915104], [1586217600000, -7.066604033442047], [1586304000000, -8.294962114584223], [1586390400000, -16.810175029429217], [1586476800000, -26.208794864259346], [1586563200000, -27.136970347747706], [1586649600000, -23.495403831086662], [1586736000000, -22.783861720975153], [1586822400000, -23.735017313010076], [1586908800000, -38.16311575000765], [1586995200000, -31.844483815449678], [1587081600000, -32.36804495707685], [1587168000000, -27.42872494081888], [1587254400000, -28.959869477958932], [1587340800000, -35.64085700144523], [1587427200000, -36.86529606304447], [1587513600000, -35.925134002400455], [1587600000000, -30.41037596252289], [1587686400000, -29.02656959784474], [1587772800000, -28.29771822128521], [1587859200000, -21.418043611348764], [1587945600000, -19.874920439349864], [1588032000000, -21.84568947480716], [1588118400000, -7.168754806180516], [1588204800000, -13.278278322697616], [1588291200000, -8.204451068423879], [1588377600000, -6.346706971915552], [1588464000000, -3.0672389325710583], [1588550400000, -5.902761858214603], [1588636800000, -2.6735836789489156], [1588723200000, -3.5706182398510293], [1588809600000, 5.454082833675784], [1588896000000, 5.357777336458099], [1588982400000, 0.7595011304194941], [1589068800000, -9.036970942617017], [1589155200000, -14.787218380914908], [1589241600000, -8.876191298473543], [1589328000000, -3.147918602563493], [1589414400000, 4.6898676199958516], [1589500800000, -1.3881648982972763], [1589587200000, -1.500482855567725], [1589673600000, 4.765137254408501], [1589760000000, 2.0506500121706495], [1589846400000, 4.68294350262363], [1589932800000, -0.4962567881849509], [1590019200000, -5.9083364071710776], [1590105600000, -3.7269803021275436], [1590192000000, -4.7564780612788695], [1590278400000, -10.251483185838026], [1590364800000, -11.48837096817445], [1590451200000, -10.383279453829402], [1590537600000, -4.795932895668244], [1590624000000, 2.0853395106797734], [1590710400000, 0.5367953513981547], [1590796800000, 4.1469788636493945], [1590883200000, 1.0605087604291725], [1590969600000, 8.211614843021067], [1591056000000, 0.1647333221179963], [1591142400000, 2.539973572275727], [1591228800000, 6.981467905457492], [1591315200000, 4.868893248938633], [1591401600000, 5.520076516810747], [1591488000000, 6.977352385261298], [1591574400000, 4.6479506819192125], [1591660800000, 4.981492680214615], [1591747200000, 6.6472418568802425], [1591833600000, 0.41375585691554306], [1591920000000, 3.4514413448794983], [1592006400000, 3.831198791351113], [1592092800000, 1.8191346287481736], [1592179200000, 0.8828316619716929], [1592265600000, 2.7420989639285835], [1592352000000, 2.2103161158236446], [1592438400000, 2.731554887695239], [1592524800000, 1.8203692948268326], [1592611200000, 2.943201621733408], [1592697600000, 1.5349117775780314], [1592784000000, 5.883293228229235], [1592870400000, 4.701447633438647], [1592956800000, -0.7549060249308468], [1593043200000, -0.32525893728706023], [1593129600000, -1.407868432666703], [1593216000000, -4.161428053417183], [1593302400000, -3.4072677901633597], [1593388800000, -5.886801718161649], [1593475200000, -6.844276404416661], [1593561600000, -6.721583808285743], [1593648000000, -8.103416741170975], [1593734400000, -9.05890538120073], [1593820800000, -9.381467373789633], [1593907200000, -9.616661250440302], [1593993600000, -8.910947097169526], [1594080000000, -10.572808750526718], [1594166400000, -10.072752131464938], [1594252800000, -12.794834756284445], [1594339200000, -12.20001975654688], [1594425600000, -14.785558661467462], [1594512000000, -12.935873962667301], [1594598400000, -17.31757757117589], [1594684800000, -16.403803694099196], [1594771200000, -19.752564761565452], [1594857600000, -21.326277666321033], [1594944000000, -20.95786456569087], [1595030400000, -22.68272225530697], [1595116800000, -21.143742637122358], [1595203200000, -26.310789930462875], [1595289600000, -21.15584138808444], [1595376000000, -20.938236491879394], [1595462400000, -20.681336057723854], [1595548800000, -20.94725749561158], [1595635200000, -20.80592760991817], [1595721600000, -16.27697894094834], [1595808000000, -6.554034189780026], [1595894400000, -4.835677019361384], [1595980800000, -4.658223100267861], [1596067200000, -5.059290724314366], [1596153600000, -2.238388174533185], [1596240000000, 0.9859977932702293], [1596326400000, -6.005014211420388], [1596412800000, -5.705386111146993], [1596499200000, -3.9618169322643837], [1596585600000, 1.734864792174477], [1596672000000, 4.5495021505879265], [1596758400000, 2.641334321675771], [1596844800000, 4.4899571811058365], [1596931200000, 2.949592440730356], [1597017600000, 3.5266023577937347], [1597104000000, 0.9347160714275162], [1597190400000, 3.4543762616762876], [1597276800000, 8.11430120892652], [1597363200000, 7.306914202409757], [1597449600000, 8.50843046841004], [1597536000000, 8.561365174590065], [1597622400000, 10.248138170502415], [1597708800000, 8.333253547285466], [1597795200000, 6.852218455431938], [1597881600000, 10.744356603874053], [1597968000000, 6.557159363645496], [1598054400000, 8.230257157183985], [1598140800000, 8.003498725263569], [1598227200000, 9.057880872570252], [1598313600000, 4.936780141989999], [1598400000000, 7.358489653106801], [1598486400000, 7.579984629154296], [1598572800000, 8.5843897946406], [1598659200000, 8.340872220040268], [1598745600000, 10.678080364680852], [1598832000000, 10.440042773694842], [1598918400000, 12.419544940338426], [1599004800000, 8.198294153953697], [1599091200000, -5.140967084119154], [1599177600000, -1.8652645701096162], [1599264000000, -5.611692640017083], [1599350400000, -4.334136847251898], [1599436800000, -2.7745149377481653], [1599523200000, -5.962110946368512], [1599609600000, -4.495649470686146], [1599696000000, -4.756509519472928], [1599782400000, -4.242105586509098], [1599868800000, -4.659099999248895], [1599955200000, -6.103960881812611], [1600041600000, -1.6800652311745239], [1600128000000, -0.5311073122548464], [1600214400000, 1.8895135122077704], [1600300800000, 0.043771974386430657], [1600387200000, 0.30817408254347356], [1600473600000, 1.0021062785736206], [1600560000000, -1.4512664118617806], [1600646400000, -7.5089934974290315], [1600732800000, -6.253440890158942], [1600819200000, -11.118452041151869], [1600905600000, -6.559866973009747], [1600992000000, -6.746199609542288], [1601078400000, -7.251564672631133], [1601164800000, -7.439938668255053], [1601251200000, -9.484094623108547], [1601337600000, -8.61605475479189], [1601424000000, -10.509710894613903], [1601510400000, -13.475982920705263], [1601596800000, -13.926927754956978], [1601683200000, -15.515019928734347], [1601769600000, -14.534564298859692], [1601856000000, -13.972862650392017], [1601942400000, -17.598171864109617], [1602028800000, -18.204072455581837], [1602115200000, -18.3122049097166], [1602201600000, -16.742009685073498], [1602288000000, -14.35092181578392], [1602374400000, -14.616936267896875], [1602460800000, -13.264882052688591], [1602547200000, -16.16955739199082], [1602633600000, -17.9217386088705], [1602720000000, -20.36918585680891], [1602806400000, -22.06463793721639], [1602892800000, -21.163301593629626], [1602979200000, -20.366556805305606], [1603065600000, -18.682144469900578], [1603152000000, -19.849213589944043], [1603238400000, -13.33102064593001], [1603324800000, -14.974587461129545], [1603411200000, -16.250373036482955], [1603497600000, -14.145844321108228], [1603584000000, -15.113334899489558], [1603670400000, -15.221142880082567], [1603756800000, -13.724723986083802], [1603843200000, -16.421348175157732], [1603929600000, -16.48793114436009], [1604016000000, -16.564135926165932], [1604102400000, -14.468710575919289], [1604188800000, -15.590148711700465], [1604275200000, -18.54680656533833], [1604361600000, -16.655058720063835], [1604448000000, -16.444940806718563], [1604534400000, -8.432594118814109], [1604620800000, -8.596676548062675], [1604707200000, -13.027561656421511], [1604793600000, -10.004339614132476], [1604880000000, -12.56286449405323], [1604966400000, -12.833149873229274], [1605052800000, -11.240289397219982], [1605139200000, -7.116758626115143], [1605225600000, -6.9066601187186905], [1605312000000, -9.665241869957526], [1605398400000, -10.798388559138914], [1605484800000, -8.62452451679502], [1605571200000, -4.253204673885193], [1605657600000, -5.383826052139511], [1605744000000, -4.643461590846201], [1605830400000, -1.0562326742365258], [1605916800000, -2.9308934048293906], [1606003200000, -4.511649696291144], [1606089600000, -5.387719748097112], [1606176000000, -2.183842145944624], [1606262400000, -5.122070715014701], [1606348800000, -11.697202875032076], [1606435200000, -11.622997482420814], [1606521600000, -11.603374678108977], [1606608000000, -10.146805864861832], [1606694400000, -5.224921015165677], [1606780800000, -8.138614731076714], [1606867200000, -8.523811780951945], [1606953600000, -8.734360041689541], [1607040000000, -11.820264896872203], [1607126400000, -12.888038267571702], [1607212800000, -12.439269809521491], [1607299200000, -12.773216412120235], [1607385600000, -16.94287504211505], [1607472000000, -18.396416774369584], [1607558400000, -21.080445534218114], [1607644800000, -22.834025605110327], [1607731200000, -22.109423129296246], [1607817600000, -20.557443391929098], [1607904000000, -19.296321948554862], [1607990400000, -19.677309113767237], [1608076800000, -16.035083051687536], [1608163200000, -13.716458894939905], [1608249600000, -13.392411713625606], [1608336000000, -13.297584789896575], [1608422400000, -13.802402697713717], [1608508800000, -15.034814401298192], [1608595200000, -12.869204974467365], [1608681600000, -15.933952223118055], [1608768000000, -14.596350194062552], [1608854400000, -13.155097610772714], [1608940800000, -10.472567346370425], [1609027200000, -10.657071203775075], [1609113600000, -8.692906613144515], [1609200000000, -8.296454816409096], [1609286400000, -6.762016954666251], [1609372800000, -7.145969340022617], [1609459200000, -7.133676756064844], [1609545600000, -3.251000976458812], [1609632000000, -1.6532216757517801], [1609718400000, -2.4716294225518993], [1609804800000, -0.40816838028057134], [1609891200000, 1.6615054671768377], [1609977600000, 3.9039554176133464], [1610064000000, 4.1208900212700925], [1610150400000, 4.0512253294429], [1610236800000, 2.8939698410513444], [1610323200000, -0.8755423028288192], [1610409600000, -2.6469863748763913], [1610496000000, 0.8236609898131917], [1610582400000, 2.3101339916353396], [1610668800000, -0.5890295126826999], [1610755200000, -1.1796551398292152], [1610841600000, -1.201114440853118], [1610928000000, -1.7308665575567943], [1611014400000, -3.041182954762199], [1611100800000, -3.388826862120517], [1611187200000, -9.35263663010825], [1611273600000, -7.737178009502671], [1611360000000, -8.882578063522232], [1611446400000, -8.634549242318705], [1611532800000, -9.552641367277808], [1611619200000, -9.362699055524395], [1611705600000, -12.461380815043547], [1611792000000, -8.940176973933141], [1611878400000, -8.65874557636647], [1611964800000, -8.728997258562302], [1612051200000, -10.032458564162539], [1612137600000, -10.993128550915621], [1612224000000, -8.533889063729866], [1612310400000, -7.111402941486276], [1612396800000, -7.479150000748838], [1612483200000, -6.713328227007054], [1612569600000, -5.948194645832942], [1612656000000, -6.678353822455264], [1612742400000, -2.1753930023743777], [1612828800000, -1.8386275900560705], [1612915200000, -3.4948602042791777], [1613001600000, -1.3579451150474426], [1613088000000, -1.9805480737290466], [1613174400000, -2.405102168430659], [1613260800000, -1.7671281190668893], [1613347200000, -2.2336053479850975], [1613433600000, -1.2889077395532524], [1613520000000, -0.5398198274867596], [1613606400000, -0.2787119562331597], [1613692800000, 1.5127534247072845], [1613779200000, 1.1791129308989312], [1613865600000, 1.8657622292593743], [1613952000000, 0.5090390339315434], [1614038400000, -2.015516613954361], [1614124800000, -1.8939914448126274], [1614211200000, -2.917903094764206], [1614297600000, -3.7336315015148287], [1614384000000, -4.220176635357383], [1614470400000, -4.726692819816961], [1614556800000, -2.213334244659862], [1614643200000, -3.2443537635569584], [1614729600000, -2.4087350436047714], [1614816000000, -3.3201531670214095], [1614902400000, -3.506818376975822], [1614988800000, -3.687844415495263], [1615075200000, -2.5874369008031124], [1615161600000, -1.612077183609017], [1615248000000, -0.7491006361266201], [1615334400000, -0.169301164242178], [1615420800000, 0.5396024115604732], [1615507200000, -0.08967357234963913], [1615593600000, 1.1432366999716308], [1615680000000, 0.40433432293865224], [1615766400000, -0.6881711772501049], [1615852800000, -0.5420973454106033], [1615939200000, 0.5692893793551264], [1616025600000, 0.04163312901946625], [1616112000000, -0.0821444442451309], [1616198400000, -0.0132026628098032], [1616284800000, -0.046641425673740855], [1616371200000, -1.438527419921435], [1616457600000, -1.6969567174767022], [1616544000000, -2.048327239610117], [1616630400000, -2.4495855894701535], [1616716800000, -0.7671901700539294], [1616803200000, -0.2156683255223939], [1616889600000, 0.07936597443036675], [1616976000000, 0.19207749626213655], [1617062400000, 0.22447956143959402], [1617148800000, 0.7266188216106144], [1617235200000, 0.8397775566470145], [1617321600000, 0.7283416091467814], [1617408000000, 0.15412406190993266], [1617494400000, 1.0815387168029602], [1617580800000, 0.8595102689594682], [1617667200000, 0.4079567102987127], [1617753600000, -0.4052148611847599], [1617840000000, 0.7659602376887236], [1617926400000, 0.4960557306345379], [1618012800000, 1.1355921311287673], [1618099200000, 1.7997832782709366], [1618185600000, 1.4371277129994553], [1618272000000, 2.68023073283355], [1618358400000, 3.12359532704032], [1618444800000, 3.61459136086129], [1618531200000, 2.643250879464233], [1618617600000, 2.580987717350105], [1618704000000, 1.5998255088720725], [1618790400000, 1.4373567963834262], [1618876800000, 2.0336834096687113], [1618963200000, 2.488991384765562], [1619049600000, 1.0890813470756413], [1619136000000, 0.9778525184026492], [1619222400000, 0.7156150072415386], [1619308800000, 1.0624844889250937], [1619395200000, 2.90322717098487], [1619481600000, 3.7761871300787178], [1619568000000, 4.983888419839026], [1619654400000, 3.955579016128546], [1619740800000, 6.614868532947057], [1619827200000, 7.11404363650162], [1619913600000, 7.145792859132861], [1620000000000, 6.749493964284177], [1620086400000, 5.495538789831521], [1620172800000, 8.591676402834253], [1620259200000, 7.276546673077675], [1620345600000, 9.268951995843864], [1620432000000, 10.69557033541166], [1620518400000, 10.825220762717315], [1620604800000, 9.686236270893922], [1620691200000, 10.365675480538961], [1620777600000, 7.240829146540648], [1620864000000, 6.566513140638328], [1620950400000, 8.198236005437387], [1621036800000, 7.5644632060513715], [1621123200000, 7.0029702696955525], [1621209600000, 4.360015531016543], [1621296000000, 4.273303214788015], [1621382400000, -1.1194264126478117], [1621468800000, 1.8481371571785132], [1621555200000, 0.7905622689074434], [1621641600000, 1.9059157631377772], [1621728000000, -1.5878004586330547], [1621814400000, 2.83591942149193], [1621900800000, 2.478159141776608], [1621987200000, 2.107284674487964], [1622073600000, 1.172667731651174], [1622160000000, 0.3924921081855359], [1622246400000, -0.05294766596450984], [1622332800000, -0.48954084463532155], [1622419200000, 2.2346685781370255], [1622505600000, 1.2580298547348576], [1622592000000, 1.31968813277431], [1622678400000, 2.939698447370972], [1622764800000, 2.1292021079922634], [1622851200000, 1.01260405628517], [1622937600000, -0.25096366851988705], [1623024000000, -1.199097291580287], [1623110400000, -2.0207867554317005], [1623196800000, 1.9643670450095172], [1623283200000, 1.8108531776403183], [1623369600000, 3.3337264976449674], [1623456000000, 1.5045850543355357], [1623542400000, 3.4231982052136374], [1623628800000, 6.259233926137064], [1623715200000, 5.386389844030624], [1623801600000, 3.990544817087354], [1623888000000, 4.435687985847302], [1623974400000, 3.1677471098730194], [1624060800000, 2.4984541984983792], [1624147200000, 1.5605989646795138], [1624233600000, -1.4554523359353055], [1624320000000, -0.5071937518277849], [1624406400000, 0.2454687083668574], [1624492800000, 2.0492004506658787], [1624579200000, -1.6865797070319957], [1624665600000, -1.227720284412655], [1624752000000, 0.5807383569241011], [1624838400000, 0.9071384133221869], [1624924800000, 2.074174374959057], [1625011200000, 0.5683316174173143], [1625097600000, -0.43367993052684994], [1625184000000, -1.0036479886660317], [1625270400000, -0.14770821355837427], [1625356800000, 0.18349407475365354], [1625443200000, -1.0564155677367921], [1625529600000, -0.35011771317202545], [1625616000000, -1.8195983201977413], [1625702400000, -2.8444449771243825], [1625788800000, -2.7988640639459987], [1625875200000, -3.4359784950905663], [1625961600000, -2.638008868324647], [1626048000000, -4.166682656140978], [1626134400000, -4.364661623424766], [1626220800000, -5.363357577549806], [1626307200000, -6.4978239186285265], [1626393600000, -8.543804044646222], [1626480000000, -8.584285679246534], [1626566400000, -8.13849699110014], [1626652800000, -9.748946601173756], [1626739200000, -11.044908654553765], [1626825600000, -8.619937606001812], [1626912000000, -8.766901451872094], [1626998400000, -8.828688479955545], [1627084800000, -8.178252132165504], [1627171200000, -6.791802113761072], [1627257600000, -5.23582247201022], [1627344000000, -2.819561235861677], [1627430400000, -2.8839847478108425], [1627516800000, -2.9392315136293945], [1627603200000, -2.825501604735294], [1627689600000, -3.418415740695913], [1627776000000, -4.441359429790921], [1627862400000, -4.971499609507589], [1627948800000, -5.247082433381976], [1628035200000, -4.442143427002009], [1628121600000, -3.53380177824738], [1628208000000, -3.3923732511866618], [1628294400000, -2.1518165543687857], [1628380800000, -2.8459095929294023], [1628467200000, -1.2019092423230546], [1628553600000, -0.5238717607064274], [1628640000000, -0.8188215656916356], [1628726400000, -1.5697249718192197], [1628812800000, -0.20019509013622638], [1628899200000, -0.5316968110755056], [1628985600000, -0.9392416180777587], [1629072000000, -1.264521513252575], [1629158400000, -1.3744935517543837], [1629244800000, -1.7523551852585442], [1629331200000, -0.4062598478103112], [1629417600000, 0.7831504499064792], [1629504000000, 0.4177132293855905], [1629590400000, 0.44000202015122625], [1629676800000, 1.4432786982580055], [1629763200000, 1.2802163391224894], [1629849600000, 1.2236753795638649], [1629936000000, -0.09111225113020538], [1630022400000, 1.5177475859077916], [1630108800000, 1.2943277328295792], [1630195200000, 0.9655717171868332], [1630281600000, 0.8913439158356624], [1630368000000, 1.914381212280965], [1630454400000, 2.182599389818833], [1630540800000, 1.8431454086820125], [1630627200000, 2.1750523682953187], [1630713600000, 2.0461714707099716], [1630800000000, 2.734120236187522], [1630886400000, 3.9153142031158055], [1630972800000, 1.2033454681934117], [1631059200000, -0.2755055343097439], [1631145600000, -0.4612903608984169], [1631232000000, -1.5520880166169846], [1631318400000, -1.5189248231263477], [1631404800000, -1.0168268329930328], [1631491200000, -1.2315600504279942], [1631577600000, 0.37841340659266365], [1631664000000, -0.15958169632342134], [1631750400000, -0.7561632521513033], [1631836800000, -1.644428376274604], [1631923200000, -1.0892230804241763], [1632009600000, -1.7923521659425674], [1632096000000, -4.504891017887111], [1632182400000, -6.056085998069172], [1632268800000, -4.906354263422472], [1632355200000, -4.082072463611773], [1632441600000, -6.139893483497858], [1632528000000, -6.242117453280798], [1632614400000, -6.002983251519005], [1632700800000, -7.229948294109072], [1632787200000, -8.052130726891605], [1632873600000, -8.20231658090664], [1632960000000, -6.519145312507199], [1633046400000, -4.531538518889903], [1633132800000, -4.835190673685396], [1633219200000, -4.500801308646359], [1633305600000, -4.427809451168663], [1633392000000, -3.409987969794834], [1633478400000, -1.925307542347987], [1633564800000, -2.3250600641096923], [1633651200000, -2.5897014825792013], [1633737600000, -2.190822593561272], [1633824000000, -2.397676915573136], [1633910400000, -1.8359331383261122], [1633996800000, -2.451917483027678], [1634083200000, -1.775920610884583], [1634169600000, -1.5749115144901324], [1634256000000, -0.09725833857103083], [1634342400000, -0.4197044346875387], [1634428800000, -0.35247523881505316], [1634515200000, -0.48795485314580134], [1634601600000, 0.49962759586655636], [1634688000000, 1.2575458597262497], [1634774400000, 0.4434167198687433], [1634860800000, -0.1933552367555933], [1634947200000, -0.1646235031170349], [1635033600000, -0.3802033087217964], [1635120000000, 0.36964171688256897], [1635206400000, -0.44925989331751026], [1635292800000, -0.8819053987171372], [1635379200000, 0.06586765681790752], [1635465600000, 1.018405511891956], [1635552000000, 0.6110815833516696], [1635638400000, 0.09775944025557948], [1635724800000, -0.011976718219656846], [1635811200000, 0.9387946299622456], [1635897600000, 0.9681753096324712], [1635984000000, 0.7321364361600331], [1636070400000, 1.2820352433535476], [1636156800000, 1.6670153620688168], [1636243200000, 1.9456485061037085], [1636329600000, 3.257269727964932], [1636416000000, 3.3199775262894207], [1636502400000, 2.7926074674910097], [1636588800000, 3.3099190833292553], [1636675200000, 3.8132127509938343], [1636761600000, 3.857999857217166], [1636848000000, 3.9052001054167036], [1636934400000, 3.83665337987987], [1637020800000, 2.526789574169918], [1637107200000, 2.5730831468446524], [1637193600000, 1.8372124808556904], [1637280000000, 3.2398343130617064], [1637366400000, 3.7969427647241503], [1637452800000, 3.1285176885800112], [1637539200000, 2.511887249844463], [1637625600000, 2.5648808947081747], [1637712000000, 2.3955031893638363], [1637798400000, 3.314536341735831], [1637884800000, 1.9513644558040824], [1637971200000, 2.5095452682490134], [1638057600000, 3.306244815236454], [1638144000000, 3.752187689033086], [1638230400000, 3.3591437975761522], [1638316800000, 3.576306003805861], [1638403200000, 3.4848496600368577], [1638489600000, 2.7669988152517746], [1638576000000, 0.32488967518972345], [1638662400000, 0.38322593989619236], [1638748800000, 1.389676536322952], [1638835200000, 1.4276151166717455], [1638921600000, 1.8336927007600465], [1639008000000, 0.30008701315417596], [1639094400000, 0.6571464688683974], [1639180800000, 1.4742730820384864], [1639267200000, 1.8107185337408538], [1639353600000, 0.2501987016925469], [1639440000000, 1.1584759794622599], [1639526400000, 1.740460532598192], [1639612800000, 1.0383971003209211], [1639699200000, 0.5593949936233287], [1639785600000, 0.7515861729335853], [1639872000000, 0.6478032779504233], [1639958400000, 1.0261250759617795], [1640044800000, 2.323080409114773], [1640131200000, 2.594190433677433], [1640217600000, 3.962382072900965], [1640304000000, 5.076863698102265], [1640390400000, 4.982428784614214], [1640476800000, 4.892883923920195], [1640563200000, 5.025721807211973], [1640649600000, 3.366874706241447], [1640736000000, 3.1226631069092647], [1640822400000, 3.8164399228724477], [1640908800000, 4.1975500152812515], [1640995200000, 5.201943720367424], [1641081600000, 4.731883167680515], [1641168000000, 4.223810458366714], [1641254400000, 3.6139096540649547], [1641340800000, 2.5593431711796484], [1641427200000, 2.562789070810801], [1641513600000, 1.4027584394560222], [1641600000000, 1.7517253308250957], [1641686400000, 1.4889586754740307], [1641772800000, 1.1743090930104287], [1641859200000, 1.6016158926921946], [1641945600000, 2.7787742310689296], [1642032000000, 2.089460112964659], [1642118400000, 2.5041385803955123], [1642204800000, 2.7830983573417853], [1642291200000, 2.436209543534005], [1642377600000, 1.3768205061583814], [1642464000000, 1.0313717099582078], [1642550400000, 1.0200542651710407], [1642636800000, 0.8697082705011425], [1642723200000, -3.032982120739547], [1642809600000, -4.3385469671932455], [1642896000000, -3.0051902548504117], [1642982400000, -2.789229802429645], [1643068800000, -3.1902093399077884], [1643155200000, -2.701062078458385], [1643241600000, -2.028273637343787], [1643328000000, -2.258055250169626], [1643414400000, -1.8531480657819728], [1643500800000, -1.6124295001215785], [1643587200000, -2.1429024913652626], [1643673600000, -2.742176804733802], [1643760000000, -3.869155125740967], [1643846400000, -2.8459764827126293], [1643932800000, 0.9876251633843793], [1644019200000, 0.850878759246676], [1644105600000, 2.309871562765089], [1644192000000, 2.5148553998837855], [1644278400000, 1.7634599832398692], [1644364800000, 1.7699180837913389], [1644451200000, 2.2259786189532136], [1644537600000, 2.154662336548519], [1644624000000, 1.9921034778126696], [1644710400000, 2.861498634308383], [1644796800000, 2.1946809037138735], [1644883200000, 2.916455683719228], [1644969600000, 1.8992062640028706], [1645056000000, 0.20974953006398067], [1645142400000, 0.21608079076766984], [1645228800000, 0.18463336200690605], [1645315200000, -0.2682005636633704], [1645401600000, -2.584842641615211], [1645488000000, -2.063093785906787], [1645574400000, -3.767968302201112], [1645660800000, -2.3725855483336105], [1645747200000, -1.1779010770889045], [1645833600000, -1.4188189377437013], [1645920000000, -2.2943630962694783], [1646006400000, 1.2797072630585191], [1646092800000, 1.6907185281516917], [1646179200000, 0.4763475553311096], [1646265600000, 0.08194649074080473], [1646352000000, -2.374404848095118], [1646438400000, -2.236863199391273], [1646524800000, -3.0146393291715867], [1646611200000, -3.7211760119391073], [1646697600000, -3.202319086446515], [1646784000000, -0.9461210693548594], [1646870400000, -2.671833259909519], [1646956800000, -3.3074418530538594], [1647043200000, -3.375159442059527], [1647129600000, -4.301177760699623], [1647216000000, -2.4237636942933705], [1647302400000, -2.915726886184032], [1647388800000, -1.501144243866264], [1647475200000, -1.4185215862677936], [1647561600000, -0.9340729011757389], [1647648000000, -0.6596203364069311], [1647734400000, -1.4865911524616635], [1647820800000, -1.4330889466008614], [1647907200000, -0.6580463536518195], [1647993600000, -0.10055034292530252], [1648080000000, 1.0935447400688716], [1648166400000, 1.3953300888785094], [1648252800000, 1.5836379405959988], [1648339200000, 2.9911588242494176], [1648425600000, 3.1915900489170426], [1648512000000, 3.719628521666152], [1648598400000, 3.47768669578344], [1648684800000, 2.880078356247509], [1648771200000, 3.7368097389982253], [1648857600000, 3.6656647139325287], [1648944000000, 4.0414154600598735], [1649030400000, 4.215917255527351], [1649116800000, 3.986491781479849], [1649203200000, 1.8700630195342853], [1649289600000, 2.9371466414951684], [1649376000000, 2.554600278867767], [1649462400000, 3.2573479579081592], [1649548800000, 3.1648644437889075], [1649635200000, 2.090326758282245], [1649721600000, 2.671441652360379], [1649808000000, 3.478369803266368], [1649894400000, 3.3559539929480167], [1649980800000, 4.150402421550773], [1650067200000, 4.124847184318099], [1650153600000, 3.4123899274218275], [1650240000000, 5.5873937037511965], [1650326400000, 6.175020689803745], [1650412800000, 6.709049149159341], [1650499200000, 6.131603002234186], [1650585600000, 6.162771345065551], [1650672000000, 5.927658669541586], [1650758400000, 5.46341241160907], [1650844800000, 8.104142172350493], [1650931200000, 5.873588426994736], [1651017600000, 7.62366054073842], [1651104000000, 8.217928207748535], [1651190400000, 7.9243432065571895], [1651276800000, 6.809721094855199], [1651363200000, 7.006488808982951], [1651449600000, 8.282648743206636], [1651536000000, 6.984636770621535], [1651622400000, 10.344071926383698], [1651708800000, 7.2612545020120365], [1651795200000, 7.488734801665096], [1651881600000, 6.459116158406417], [1651968000000, 4.2716668043796915], [1652054400000, -0.4776421899488099], [1652140800000, 0.3608576317119656], [1652227200000, -0.6851588485682214], [1652313600000, -1.4245860966156698], [1652400000000, 0.1648054502207117], [1652486400000, 1.174724463699846], [1652572800000, 2.9434701364845495], [1652659200000, 2.374207418365728], [1652745600000, 3.177359189351151], [1652832000000, 1.5411429470727143], [1652918400000, 4.985266450563131], [1653004800000, 4.270290064033645], [1653091200000, 5.733021719904158], [1653177600000, 6.177348394566835], [1653264000000, 5.463214988411721], [1653350400000, 6.359448145222956], [1653436800000, 7.345139437047862], [1653523200000, 7.337997379765227], [1653609600000, 6.980190736224969], [1653696000000, 8.675289818359389], [1653782400000, 9.036426064777146], [1653868800000, 13.564390748047103], [1653955200000, 14.133983140172461], [1654041600000, 12.367325226717014], [1654128000000, 13.950019048939254], [1654214400000, 13.693244657551588], [1654300800000, 15.098060693278256], [1654387200000, 14.900386779372624], [1654473600000, 18.196874105154038], [1654560000000, 18.3731666431717], [1654646400000, 17.34638710542103], [1654732800000, 17.246466789532974], [1654819200000, 16.298866358770155], [1654905600000, 16.31550993153617], [1654992000000, 13.089708802837862], [1655078400000, 5.326869753687276], [1655164800000, 5.2407583227189605], [1655251200000, 5.95597996389472], [1655337600000, -1.1048703708421073], [1655424000000, -0.6800097988744938], [1655510400000, -5.444477888817701], [1655596800000, 0.23703485430770854], [1655683200000, -0.6350071191718882], [1655769600000, 0.07553788219252056], [1655856000000, -2.7326096586287463], [1655942400000, -0.37354165060195044], [1656028800000, 0.5313586704671422], [1656115200000, 1.0889321771181386], [1656201600000, 0.5692119425469144], [1656288000000, -0.5659116875707042], [1656374400000, -1.822374663993088], [1656460800000, -4.122139372020271], [1656547200000, -6.018033110722783], [1656633600000, -7.851427882400117], [1656720000000, -7.965364225362748], [1656806400000, -6.917628991835301], [1656892800000, -3.8215991568816463], [1656979200000, -3.8413324804320155], [1657065600000, -4.26403755615884], [1657152000000, -2.0619413083707627], [1657238400000, -2.3564643427854435], [1657324800000, -2.2344353790467295], [1657411200000, -3.869055486132737], [1657497600000, -6.930535795725859], [1657584000000, -8.82052152668416], [1657670400000, -7.343613147063891], [1657756800000, -6.698764301411046], [1657843200000, -6.3388318410867015], [1657929600000, -4.9993724294047155], [1658016000000, -6.012823485105656], [1658102400000, -1.382515636350064], [1658188800000, 1.3483265345048778], [1658275200000, -0.08466885910664246], [1658361600000, -0.5092793679692704], [1658448000000, -0.6897600754572153], [1658534400000, -1.1800119025820948], [1658620800000, -0.992105427554506], [1658707200000, -4.186009970636093], [1658793600000, -3.7657555584837326], [1658880000000, 0.2811861500691606], [1658966400000, 2.2310494023198544], [1659052800000, 3.7208174780769383], [1659139200000, 3.592713225497775], [1659225600000, 2.9528998129765966], [1659312000000, 2.184562441226163], [1659398400000, 2.3155215737641157], [1659484800000, 1.7276259152350661], [1659571200000, 1.1788312544234714], [1659657600000, 4.863527493941874], [1659744000000, 4.102451643638091], [1659830400000, 4.6485297172988425], [1659916800000, 5.7702329789781], [1660003200000, 5.554378310638796], [1660089600000, 7.017203066948198], [1660176000000, 6.851375288725066], [1660262400000, 8.746220472933132], [1660348800000, 8.677688463246], [1660435200000, 8.301818536214085], [1660521600000, 7.2442954941055575], [1660608000000, 9.21479919215217], [1660694400000, 7.6284644353806215], [1660780800000, 7.517690762069236], [1660867200000, 1.3750444504256336], [1660953600000, 2.013982906414981], [1661040000000, 3.594094224419493], [1661126400000, 2.4995877691904127], [1661212800000, 5.848402081511537], [1661299200000, 5.202682559615894], [1661385600000, 5.242091754464738], [1661472000000, 0.48374449453325497], [1661558400000, -0.1361825849586893], [1661644800000, -1.1815703464703091], [1661731200000, 0.3502263120219027], [1661817600000, 1.8030207540817003], [1661904000000, 2.1354855463081748], [1661990400000, 1.8319298838338938], [1662076800000, 0.05147505940459496], [1662163200000, -0.33439424451880484], [1662249600000, 0.8515350043907688], [1662336000000, -0.9590128718636493], [1662422400000, -2.517658041987559], [1662508800000, -0.7769550594670847], [1662595200000, -1.03564035749568], [1662681600000, 5.122398533125093], [1662768000000, 6.064761943546472], [1662854400000, 7.295408149970541], [1662940800000, 7.992180941172535], [1663027200000, 2.5057124478151707], [1663113600000, 2.809683757011811], [1663200000000, 0.3487689055265406], [1663286400000, 1.3404108010563647], [1663372800000, 2.7956323460493593], [1663459200000, 0.8564796063703142], [1663545600000, 0.4772332797003287], [1663632000000, -1.7534362268437889], [1663718400000, -3.155053317955179], [1663804800000, -0.25394490277660964], [1663891200000, -0.10576817071250844], [1663977600000, -1.0328731200513772], [1664064000000, -1.6514992152657442], [1664150400000, -0.549307221075594], [1664236800000, -1.8647354415939787], [1664323200000, -1.098354180914768], [1664409600000, -0.19429101231089874], [1664496000000, -0.5364573125840053], [1664582400000, -0.8841233672118847], [1664668800000, -2.0049108285480486], [1664755200000, 0.058300184484650686], [1664841600000, 1.7818606233888659], [1664928000000, 1.1060416035250569], [1665014400000, 0.7247909638108325], [1665100800000, -1.3370542648649035], [1665187200000, -1.8687799770174394], [1665273600000, -1.8506405291275172], [1665360000000, -2.5414947943860398], [1665446400000, -1.6137829110522688], [1665532800000, 1.2744242808575592], [1665619200000, 0.5195127211682831], [1665705600000, -0.4980868552208335], [1665792000000, -0.8914437089377287], [1665878400000, 0.30726171861175544], [1665964800000, 1.3673437565669389], [1666051200000, 1.393648555460416], [1666137600000, 3.411923594351208], [1666224000000, 1.612920941546875], [1666310400000, 1.690138423455906], [1666396800000, 1.8043521614179667], [1666483200000, 4.245257752496599], [1666569600000, 4.0680543540860725], [1666656000000, 7.068776486427865], [1666742400000, 11.682907905889195], [1666828800000, 8.499540855693624], [1666915200000, 9.32077321875687], [1667001600000, 10.104548652453687], [1667088000000, 10.82797765438653], [1667174400000, 11.146181499977274], [1667260800000, 11.624066377214945], [1667347200000, 12.445843517067232], [1667433600000, 10.959572840123386], [1667520000000, 13.997341302660573], [1667606400000, 14.87738679309551], [1667692800000, 14.624670003027461], [1667779200000, 14.40453675586376], [1667865600000, 7.088604332601477], [1667952000000, -4.2662253138711606], [1668038400000, 2.697931171298819], [1668124800000, 0.6419060327537807], [1668211200000, -0.043100581145125716], [1668297600000, -1.703140303668249], [1668384000000, 0.3224237441669686], [1668470400000, 0.11415480889408514], [1668556800000, -1.7707478649577126], [1668643200000, -1.4272318722415775], [1668729600000, -0.6742280142328809], [1668816000000, -0.5128877280562563], [1668902400000, -2.4532682567617883], [1668988800000, -4.091040289409847], [1669075200000, -3.4861022764632708], [1669161600000, -2.2452239244458667], [1669248000000, -2.042780486689196], [1669334400000, -1.6651751922986477], [1669420800000, -1.8853115860001708], [1669507200000, -2.1573900766996132], [1669593600000, -2.823509769189201], [1669680000000, -2.758982346019735], [1669766400000, 0.6907996383743296], [1669852800000, -0.09688632271354436], [1669939200000, 1.2236224115317498], [1670025600000, 0.2891322973994477], [1670112000000, 1.1720787481313835], [1670198400000, 0.6541256212744031], [1670284800000, 0.341530316045521], [1670371200000, -0.6090226731973303], [1670457600000, 1.2720514565222913], [1670544000000, 1.5295687319238596], [1670630400000, 1.4308716397376315], [1670716800000, 1.0849491355430132], [1670803200000, 1.6349119552125444], [1670889600000, 3.2568561766448454], [1670976000000, 2.9629560552804435], [1671062400000, 0.47564279588237923], [1671148800000, -3.1906850071187307], [1671235200000, -3.374388112345457], [1671321600000, -3.729153497520457], [1671408000000, -5.390764441109241], [1671494400000, -3.494631964267654], [1671580800000, -3.986525439331473], [1671667200000, -5.121338191668997], [1671753600000, -7.138701175297825], [1671840000000, -7.602006857106971], [1671926400000, -7.801359182000937], [1672012800000, -7.88343088882371], [1672099200000, -8.82426652599392], [1672185600000, -10.061135313555553], [1672272000000, -10.670114833907448], [1672358400000, -12.747219884766608], [1672444800000, -13.770733273562243], [1672531200000, -13.881805991619714], [1672617600000, -13.539079606765185], [1672704000000, -13.763826517324901], [1672790400000, -13.745372779630344], [1672876800000, -14.705821545201445], [1672963200000, -16.026957489750885], [1673049600000, -16.7268958724365], [1673136000000, -16.115857062179273], [1673222400000, -15.598791556054522], [1673308800000, -14.82758201004819], [1673395200000, -13.099525400423872], [1673481600000, -9.441741490356222], [1673568000000, -7.00067034255224], [1673654400000, -4.3076300268851355], [1673740800000, -4.587382069467424], [1673827200000, -3.309294326292843], [1673913600000, -3.9678173918985777], [1674000000000, -6.694075069584855], [1674086400000, -4.401459276389716], [1674172800000, -1.0027112746694655], [1674259200000, -0.8358568075416173]], &quot;type&quot;: &quot;bar&quot;, &quot;dataLabels&quot;: {&quot;enabled&quot;: true, &quot;format&quot;: &quot;{point.properties.postal-code}&quot;}, &quot;name&quot;: &quot;outperf&quot;}]; var dataLen = data.length; for (var ix = 0; ix &lt; dataLen; ix++) { chart.addSeries(data[ix]); } }); &lt;/script&gt; &lt;/body&gt; &lt;/html&gt;\" height=520 width=820></iframe>"
      ],
      "text/plain": [
       "<highcharts.highcharts.highcharts.Highchart at 0x10cb6bd90>"
      ]
     },
     "execution_count": 350,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create summary HTML table\n",
    "heading = f'<h1>Summary Results for DCA</h1>'\n",
    "display(HTML(heading))\n",
    "        \n",
    "table_stats = f\"\"\"\n",
    "        <h3>Inputs</h3>\n",
    "        <table>\n",
    "        <thead>\n",
    "        \"\"\"\n",
    "\n",
    "for key, value in stats['inputs'].items():\n",
    "    table_stats += f\"\"\"\n",
    "            <tr>\n",
    "                <td style='text-align: left;'>\n",
    "                {key}\n",
    "                </td>\n",
    "                <td style='text-align: right;'>\n",
    "                {value}\n",
    "                </td>\n",
    "            </tr>       \n",
    "            \"\"\"\n",
    "\n",
    "table_stats += f\"\"\"\n",
    "        </thead>\n",
    "        </table>\n",
    "        \"\"\"\n",
    "display(HTML(table_stats))\n",
    "\n",
    "\n",
    "table_stats = f\"\"\"\n",
    "        <h3>Outputs</h3>\n",
    "        <table>\n",
    "        <thead>\n",
    "        \"\"\"\n",
    "\n",
    "for key, value in stats['outputs'].items():\n",
    "    table_stats += f\"\"\"\n",
    "            <tr>\n",
    "                <td style='text-align: left;'>\n",
    "                {key}\n",
    "                </td>\n",
    "                <td style='text-align: right;'>\n",
    "                {\"{0:,.2f}\".format(value)}\n",
    "                </td>\n",
    "            </tr>       \n",
    "            \"\"\"\n",
    "\n",
    "table_stats += f\"\"\"\n",
    "        </thead>\n",
    "        </table>\n",
    "        \"\"\"\n",
    "\n",
    "\n",
    "        \n",
    "display(HTML(table_stats))\n",
    "        \n",
    "\n",
    "# Chart Outperformance along time\n",
    "# dates need to be in Epoch time for Highcharts\n",
    "df_chart = deepcopy(d)\n",
    "df_chart['start_date'] = (df_chart['start_date'] - datetime(1970, 1, 1)).astype(np.int64)\n",
    "df_chart['start_date'] = (df_chart['start_date'] / 1000000).astype(np.int64)\n",
    "x = df_chart['start_date'].to_list()\n",
    "y = df_chart['outperformance_DV100'].to_list()\n",
    "plot_chart(x, y, 'dates', 'outperformance', 'bar', 'outperf', 'Outperformance of $100 invested lumpsum compared to cost average')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 351,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>close</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>change</th>\n",
       "      <th>allocation</th>\n",
       "      <th>BTC_tx</th>\n",
       "      <th>BTC_position</th>\n",
       "      <th>portfolio_position</th>\n",
       "      <th>cum_capital</th>\n",
       "      <th>normalized_port_position</th>\n",
       "      <th>cum_return</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-01-01</th>\n",
       "      <td>995.44</td>\n",
       "      <td>963.38</td>\n",
       "      <td>1,001.61</td>\n",
       "      <td>956.10</td>\n",
       "      <td>0.03</td>\n",
       "      <td>50,000.00</td>\n",
       "      <td>50.23</td>\n",
       "      <td>50.23</td>\n",
       "      <td>50,000.00</td>\n",
       "      <td>50,000.00</td>\n",
       "      <td>100.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-08</th>\n",
       "      <td>900.86</td>\n",
       "      <td>888.87</td>\n",
       "      <td>936.13</td>\n",
       "      <td>875.85</td>\n",
       "      <td>0.01</td>\n",
       "      <td>12,500.00</td>\n",
       "      <td>13.88</td>\n",
       "      <td>64.10</td>\n",
       "      <td>57,749.34</td>\n",
       "      <td>62,500.00</td>\n",
       "      <td>92.40</td>\n",
       "      <td>0.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-15</th>\n",
       "      <td>821.17</td>\n",
       "      <td>819.63</td>\n",
       "      <td>826.43</td>\n",
       "      <td>808.63</td>\n",
       "      <td>0.00</td>\n",
       "      <td>12,500.00</td>\n",
       "      <td>15.22</td>\n",
       "      <td>79.33</td>\n",
       "      <td>65,140.84</td>\n",
       "      <td>75,000.00</td>\n",
       "      <td>86.85</td>\n",
       "      <td>0.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-22</th>\n",
       "      <td>918.84</td>\n",
       "      <td>919.84</td>\n",
       "      <td>938.38</td>\n",
       "      <td>888.62</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>12,500.00</td>\n",
       "      <td>13.60</td>\n",
       "      <td>92.93</td>\n",
       "      <td>85,388.69</td>\n",
       "      <td>87,500.00</td>\n",
       "      <td>97.59</td>\n",
       "      <td>0.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-29</th>\n",
       "      <td>914.55</td>\n",
       "      <td>918.51</td>\n",
       "      <td>922.40</td>\n",
       "      <td>912.68</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>12,500.00</td>\n",
       "      <td>13.67</td>\n",
       "      <td>106.60</td>\n",
       "      <td>97,490.02</td>\n",
       "      <td>100,000.00</td>\n",
       "      <td>97.49</td>\n",
       "      <td>0.97</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            close   open     high    low  change  allocation  BTC_tx  \\\n",
       "date                                                                   \n",
       "2017-01-01 995.44 963.38 1,001.61 956.10    0.03   50,000.00   50.23   \n",
       "2017-01-08 900.86 888.87   936.13 875.85    0.01   12,500.00   13.88   \n",
       "2017-01-15 821.17 819.63   826.43 808.63    0.00   12,500.00   15.22   \n",
       "2017-01-22 918.84 919.84   938.38 888.62   -0.00   12,500.00   13.60   \n",
       "2017-01-29 914.55 918.51   922.40 912.68   -0.00   12,500.00   13.67   \n",
       "\n",
       "            BTC_position  portfolio_position  cum_capital  \\\n",
       "date                                                        \n",
       "2017-01-01         50.23           50,000.00    50,000.00   \n",
       "2017-01-08         64.10           57,749.34    62,500.00   \n",
       "2017-01-15         79.33           65,140.84    75,000.00   \n",
       "2017-01-22         92.93           85,388.69    87,500.00   \n",
       "2017-01-29        106.60           97,490.02   100,000.00   \n",
       "\n",
       "            normalized_port_position  cum_return  \n",
       "date                                              \n",
       "2017-01-01                    100.00        1.00  \n",
       "2017-01-08                     92.40        0.92  \n",
       "2017-01-15                     86.85        0.87  \n",
       "2017-01-22                     97.59        0.98  \n",
       "2017-01-29                     97.49        0.97  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total allocation:\n",
      "100000.0\n",
      "Checks [OK]\n"
     ]
    }
   ],
   "source": [
    "# Show only the allocation periods\n",
    "al_df = btc_alloc.show_allocations()\n",
    "display(al_df)\n",
    "# Check it adds to allocation amount\n",
    "print(\"Total allocation:\")\n",
    "print(round(al_df.allocation.sum(), 8))\n",
    "if (round(al_df.allocation.sum(), 8) == round(btc_alloc.capital, 8)):\n",
    "    print (\"Checks [OK]\")\n",
    "else:\n",
    "    print (\"[ERROR] - something went wrong\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Run Simulations\n",
    "Create different allocation scenarios"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 352,
   "metadata": {},
   "outputs": [],
   "source": [
    "# CONSTANTS\n",
    "# Define some static variables that will remain constant\n",
    "\n",
    "# --------------\n",
    "# Start Date\n",
    "# --------------\n",
    "# Data from 2010 has less meaning than recent data. For this analysis we can use\n",
    "# more recent data. Using only data since 2017.\n",
    "sim_start_date = pd.to_datetime('2017-01-01', format='%Y-%m-%d')\n",
    "\n",
    "# Assuming $100,000 to be allocated\n",
    "sim_allocated_capital = 10000\n",
    "\n",
    "# Risk Free Rate (used to calculate sharpe ratio)\n",
    "sim_risk_free_rate = 0.05\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 353,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Variables\n",
    "# These will be the ranges / variables to be simulated\n",
    "\n",
    "sim_frequencies = ['D', 'W', 'M']\n",
    "sim_allocation_periods = {\n",
    "    'D': [10, 15, 30],\n",
    "    'W': [4, 8],\n",
    "    'M': [6, 12]\n",
    "}\n",
    "sim_upfront_percents = [0, 0.25, 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 354,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running scenarios...\n",
      "Running scenario: D 0 10\n",
      "Running scenario: D 0.25 10\n",
      "Running scenario: D 1 10\n",
      "Running scenario: D 0 15\n",
      "Running scenario: D 0.25 15\n",
      "Running scenario: D 1 15\n",
      "Running scenario: D 0 30\n",
      "Running scenario: D 0.25 30\n",
      "Running scenario: D 1 30\n",
      "Running scenario: W 0 4\n",
      "Running scenario: W 0.25 4\n",
      "Running scenario: W 1 4\n",
      "Running scenario: W 0 8\n",
      "Running scenario: W 0.25 8\n",
      "Running scenario: W 1 8\n",
      "Running scenario: M 0 6\n",
      "Running scenario: M 0.25 6\n",
      "Running scenario: M 1 6\n",
      "Running scenario: M 0 12\n",
      "Running scenario: M 0.25 12\n",
      "Running scenario: M 1 12\n"
     ]
    }
   ],
   "source": [
    "# Loop to gather results\n",
    "print(\"Running scenarios...\")\n",
    "sim_results =  []\n",
    "full_df = pd.DataFrame()\n",
    "for freq in sim_frequencies:\n",
    "    for all in sim_allocation_periods[freq]:\n",
    "        for upfr in sim_upfront_percents:\n",
    "            # Create allocation instance\n",
    "            sim_alloc = AllocationManager()\n",
    "            sim_alloc.capital = sim_allocated_capital\n",
    "            sim_alloc.allocation_periods = all\n",
    "            sim_alloc.frequency = freq\n",
    "            sim_alloc.start_date = sim_start_date\n",
    "            sim_alloc.upfront_percent = upfr\n",
    "            sim_alloc.allocate_capital()\n",
    "            print('Running scenario: ' + str(freq) + ' ' + str(upfr) + ' ' + str(all))\n",
    "            # Run this allocation through time\n",
    "            tmp_df, stats = run_through_time(sim_alloc)\n",
    "            full_df = pd.concat([full_df, tmp_df])\n",
    "            sim_results.append(stats['inputs'] | stats['outputs'])\n",
    "\n",
    "sim_df = pd.DataFrame(sim_results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 355,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'frequency': 'D',\n",
       "  'allocation_periods': 10,\n",
       "  'upfront_percent': 0,\n",
       "  'capital': 10000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-02-25 00:00:00'),\n",
       "  'risk_free_rate': 0.05,\n",
       "  'number_of_allocations': 2237,\n",
       "  'avg_BTC_allocated': 1.5654553408188887,\n",
       "  'avg_lump_sum_beats_avg': 0.5561019222172553,\n",
       "  'avg_ROIC': 2.5987908429910456,\n",
       "  'avg_sharpe': 0.38199004676061576,\n",
       "  'avg_DD': 0.35795652273184375,\n",
       "  'avg_DaR_DD_abs_95': 0.6724150541591273,\n",
       "  'avg_outperformance_DV100': -4.458561678611549,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.01029765400327},\n",
       " {'frequency': 'D',\n",
       "  'allocation_periods': 10,\n",
       "  'upfront_percent': 0.25,\n",
       "  'capital': 10000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-02-25 00:00:00'),\n",
       "  'risk_free_rate': 0.05,\n",
       "  'number_of_allocations': 2237,\n",
       "  'avg_BTC_allocated': 1.5686877594731279,\n",
       "  'avg_lump_sum_beats_avg': 0.5561019222172553,\n",
       "  'avg_ROIC': 2.606221779122065,\n",
       "  'avg_sharpe': 0.3870770115039016,\n",
       "  'avg_DD': 0.35841461642328243,\n",
       "  'avg_DaR_DD_abs_95': 0.6726545238994934,\n",
       "  'avg_outperformance_DV100': -3.7154680655096133,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.01029765400327},\n",
       " {'frequency': 'D',\n",
       "  'allocation_periods': 10,\n",
       "  'upfront_percent': 1,\n",
       "  'capital': 10000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-02-25 00:00:00'),\n",
       "  'risk_free_rate': 0.05,\n",
       "  'number_of_allocations': 2237,\n",
       "  'avg_BTC_allocated': 1.584849852744322,\n",
       "  'avg_lump_sum_beats_avg': 0.0,\n",
       "  'avg_ROIC': 2.643376459777161,\n",
       "  'avg_sharpe': 0.43287741815031383,\n",
       "  'avg_DD': 0.3606817487605796,\n",
       "  'avg_DaR_DD_abs_95': 0.6740782843452864,\n",
       "  'avg_outperformance_DV100': 5.495033226933274e-16,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.0},\n",
       " {'frequency': 'D',\n",
       "  'allocation_periods': 15,\n",
       "  'upfront_percent': 0,\n",
       "  'capital': 10000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-02-25 00:00:00'),\n",
       "  'risk_free_rate': 0.05,\n",
       "  'number_of_allocations': 2232,\n",
       "  'avg_BTC_allocated': 1.5559551364927064,\n",
       "  'avg_lump_sum_beats_avg': 0.5604838709677419,\n",
       "  'avg_ROIC': 2.5769510322700797,\n",
       "  'avg_sharpe': 0.3637017277649809,\n",
       "  'avg_DD': 0.357478802152197,\n",
       "  'avg_DaR_DD_abs_95': 0.6729247071463853,\n",
       "  'avg_outperformance_DV100': -7.228353676980029,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.0162678082098144},\n",
       " {'frequency': 'D',\n",
       "  'allocation_periods': 15,\n",
       "  'upfront_percent': 0.25,\n",
       "  'capital': 10000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-02-25 00:00:00'),\n",
       "  'risk_free_rate': 0.05,\n",
       "  'number_of_allocations': 2232,\n",
       "  'avg_BTC_allocated': 1.5621314328709817,\n",
       "  'avg_lump_sum_beats_avg': 0.5604838709677419,\n",
       "  'avg_ROIC': 2.5911495841355765,\n",
       "  'avg_sharpe': 0.37157433513205185,\n",
       "  'avg_DD': 0.3582654450533404,\n",
       "  'avg_DaR_DD_abs_95': 0.6733492583903193,\n",
       "  'avg_outperformance_DV100': -5.808498490430389,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.0162678082098144},\n",
       " {'frequency': 'D',\n",
       "  'allocation_periods': 15,\n",
       "  'upfront_percent': 1,\n",
       "  'capital': 10000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-02-25 00:00:00'),\n",
       "  'risk_free_rate': 0.05,\n",
       "  'number_of_allocations': 2232,\n",
       "  'avg_BTC_allocated': 1.5873980998730164,\n",
       "  'avg_lump_sum_beats_avg': 0.0,\n",
       "  'avg_ROIC': 2.64923456903988,\n",
       "  'avg_sharpe': 0.42628555302497956,\n",
       "  'avg_DD': 0.3614391798790765,\n",
       "  'avg_DaR_DD_abs_95': 0.675421527370798,\n",
       "  'avg_outperformance_DV100': 5.380005481337677e-16,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.0},\n",
       " {'frequency': 'D',\n",
       "  'allocation_periods': 30,\n",
       "  'upfront_percent': 0,\n",
       "  'capital': 10000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-02-25 00:00:00'),\n",
       "  'risk_free_rate': 0.05,\n",
       "  'number_of_allocations': 2217,\n",
       "  'avg_BTC_allocated': 1.5263843287607022,\n",
       "  'avg_lump_sum_beats_avg': 0.5548037889039242,\n",
       "  'avg_ROIC': 2.5089713529327446,\n",
       "  'avg_sharpe': 0.32013963636258885,\n",
       "  'avg_DD': 0.35652394113433994,\n",
       "  'avg_DaR_DD_abs_95': 0.6747774828334581,\n",
       "  'avg_outperformance_DV100': -15.818942128815161,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.0359390463440177},\n",
       " {'frequency': 'D',\n",
       "  'allocation_periods': 30,\n",
       "  'upfront_percent': 0.25,\n",
       "  'capital': 10000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-02-25 00:00:00'),\n",
       "  'risk_free_rate': 0.05,\n",
       "  'number_of_allocations': 2217,\n",
       "  'avg_BTC_allocated': 1.5418076133365117,\n",
       "  'avg_lump_sum_beats_avg': 0.5548037889039242,\n",
       "  'avg_ROIC': 2.544427602531813,\n",
       "  'avg_sharpe': 0.33474560491594363,\n",
       "  'avg_DD': 0.3582345920090399,\n",
       "  'avg_DaR_DD_abs_95': 0.6758581859844167,\n",
       "  'avg_outperformance_DV100': -12.273317168908278,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.0359390463440177},\n",
       " {'frequency': 'D',\n",
       "  'allocation_periods': 30,\n",
       "  'upfront_percent': 1,\n",
       "  'capital': 10000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-02-25 00:00:00'),\n",
       "  'risk_free_rate': 0.05,\n",
       "  'number_of_allocations': 2217,\n",
       "  'avg_BTC_allocated': 1.5951959060989302,\n",
       "  'avg_lump_sum_beats_avg': 0.0,\n",
       "  'avg_ROIC': 2.6671607742208963,\n",
       "  'avg_sharpe': 0.4268989722066769,\n",
       "  'avg_DD': 0.3636652885337802,\n",
       "  'avg_DaR_DD_abs_95': 0.6794674447801491,\n",
       "  'avg_outperformance_DV100': 5.480505539692247e-16,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.0},\n",
       " {'frequency': 'W',\n",
       "  'allocation_periods': 4,\n",
       "  'upfront_percent': 0,\n",
       "  'capital': 10000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-02-25 00:00:00'),\n",
       "  'risk_free_rate': 0.05,\n",
       "  'number_of_allocations': 2219,\n",
       "  'avg_BTC_allocated': 1.5445532133942634,\n",
       "  'avg_lump_sum_beats_avg': 0.5538530869761153,\n",
       "  'avg_ROIC': 2.550739402101377,\n",
       "  'avg_sharpe': 0.3404725961654389,\n",
       "  'avg_DD': 0.3591267103153708,\n",
       "  'avg_DaR_DD_abs_95': 0.6760525353441718,\n",
       "  'avg_outperformance_DV100': -11.401487783149335,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.0256081608348497},\n",
       " {'frequency': 'W',\n",
       "  'allocation_periods': 4,\n",
       "  'upfront_percent': 0.25,\n",
       "  'capital': 10000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-02-25 00:00:00'),\n",
       "  'risk_free_rate': 0.05,\n",
       "  'number_of_allocations': 2219,\n",
       "  'avg_BTC_allocated': 1.5445532133942634,\n",
       "  'avg_lump_sum_beats_avg': 0.5538530869761153,\n",
       "  'avg_ROIC': 2.550739402101377,\n",
       "  'avg_sharpe': 0.3404725961654389,\n",
       "  'avg_DD': 0.3591267103153708,\n",
       "  'avg_DaR_DD_abs_95': 0.6760525353441718,\n",
       "  'avg_outperformance_DV100': -11.401487783149335,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.0256081608348497},\n",
       " {'frequency': 'W',\n",
       "  'allocation_periods': 4,\n",
       "  'upfront_percent': 1,\n",
       "  'capital': 10000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-02-25 00:00:00'),\n",
       "  'risk_free_rate': 0.05,\n",
       "  'number_of_allocations': 2219,\n",
       "  'avg_BTC_allocated': 1.5941490935721123,\n",
       "  'avg_lump_sum_beats_avg': 0.0,\n",
       "  'avg_ROIC': 2.6647542799328705,\n",
       "  'avg_sharpe': 0.4263710120953863,\n",
       "  'avg_DD': 0.3633686218209015,\n",
       "  'avg_DaR_DD_abs_95': 0.6789294068503399,\n",
       "  'avg_outperformance_DV100': 5.539607628954363e-16,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.0},\n",
       " {'frequency': 'W',\n",
       "  'allocation_periods': 8,\n",
       "  'upfront_percent': 0,\n",
       "  'capital': 10000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-02-25 00:00:00'),\n",
       "  'risk_free_rate': 0.05,\n",
       "  'number_of_allocations': 2191,\n",
       "  'avg_BTC_allocated': 1.4925443448825217,\n",
       "  'avg_lump_sum_beats_avg': 0.5659516202647193,\n",
       "  'avg_ROIC': 2.4311773584748413,\n",
       "  'avg_sharpe': 0.2757734660884696,\n",
       "  'avg_DD': 0.3583645190549263,\n",
       "  'avg_DaR_DD_abs_95': 0.6798273921605648,\n",
       "  'avg_outperformance_DV100': -26.541492293869265,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.0628429820418235},\n",
       " {'frequency': 'W',\n",
       "  'allocation_periods': 8,\n",
       "  'upfront_percent': 0.25,\n",
       "  'capital': 10000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-02-25 00:00:00'),\n",
       "  'risk_free_rate': 0.05,\n",
       "  'number_of_allocations': 2191,\n",
       "  'avg_BTC_allocated': 1.509037789755486,\n",
       "  'avg_lump_sum_beats_avg': 0.5659516202647193,\n",
       "  'avg_ROIC': 2.4690937760375125,\n",
       "  'avg_sharpe': 0.28236803421257256,\n",
       "  'avg_DD': 0.3593390093049894,\n",
       "  'avg_DaR_DD_abs_95': 0.6805527791719501,\n",
       "  'avg_outperformance_DV100': -22.749850537602253,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.0628429820418235},\n",
       " {'frequency': 'W',\n",
       "  'allocation_periods': 8,\n",
       "  'upfront_percent': 1,\n",
       "  'capital': 10000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-02-25 00:00:00'),\n",
       "  'risk_free_rate': 0.05,\n",
       "  'number_of_allocations': 2191,\n",
       "  'avg_BTC_allocated': 1.6079984589932719,\n",
       "  'avg_lump_sum_beats_avg': 0.0,\n",
       "  'avg_ROIC': 2.696592281413534,\n",
       "  'avg_sharpe': 0.3435411080582899,\n",
       "  'avg_DD': 0.36768678915900604,\n",
       "  'avg_DaR_DD_abs_95': 0.6865520076172181,\n",
       "  'avg_outperformance_DV100': 5.350960812433434e-16,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.0},\n",
       " {'frequency': 'M',\n",
       "  'allocation_periods': 6,\n",
       "  'upfront_percent': 0,\n",
       "  'capital': 10000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-02-25 00:00:00'),\n",
       "  'risk_free_rate': 0.05,\n",
       "  'number_of_allocations': 2063,\n",
       "  'avg_BTC_allocated': 1.3469379246506028,\n",
       "  'avg_lump_sum_beats_avg': 0.5492001938923897,\n",
       "  'avg_ROIC': 2.096445962344928,\n",
       "  'avg_sharpe': 0.1453682189093728,\n",
       "  'avg_DD': 0.37269118427226144,\n",
       "  'avg_DaR_DD_abs_95': 0.7046694013707515,\n",
       "  'avg_outperformance_DV100': -75.205719898321,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.2541350033559715},\n",
       " {'frequency': 'M',\n",
       "  'allocation_periods': 6,\n",
       "  'upfront_percent': 0.25,\n",
       "  'capital': 10000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-02-25 00:00:00'),\n",
       "  'risk_free_rate': 0.05,\n",
       "  'number_of_allocations': 2063,\n",
       "  'avg_BTC_allocated': 1.3796520225271849,\n",
       "  'avg_lump_sum_beats_avg': 0.5492001938923897,\n",
       "  'avg_ROIC': 2.171651682243249,\n",
       "  'avg_sharpe': 0.14673308915654953,\n",
       "  'avg_DD': 0.37343085055045594,\n",
       "  'avg_DaR_DD_abs_95': 0.7056195638954155,\n",
       "  'avg_outperformance_DV100': -67.68514790848889,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.2541350033559715},\n",
       " {'frequency': 'M',\n",
       "  'allocation_periods': 6,\n",
       "  'upfront_percent': 1,\n",
       "  'capital': 10000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-02-25 00:00:00'),\n",
       "  'risk_free_rate': 0.05,\n",
       "  'number_of_allocations': 2063,\n",
       "  'avg_BTC_allocated': 1.6740789034164218,\n",
       "  'avg_lump_sum_beats_avg': 0.0,\n",
       "  'avg_ROIC': 2.848503161328137,\n",
       "  'avg_sharpe': 0.14495050291277903,\n",
       "  'avg_DD': 0.38545975461278714,\n",
       "  'avg_DaR_DD_abs_95': 0.7184901442521773,\n",
       "  'avg_outperformance_DV100': 6.785114830089178e-16,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.0},\n",
       " {'frequency': 'M',\n",
       "  'allocation_periods': 12,\n",
       "  'upfront_percent': 0,\n",
       "  'capital': 10000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-02-25 00:00:00'),\n",
       "  'risk_free_rate': 0.05,\n",
       "  'number_of_allocations': 1882,\n",
       "  'avg_BTC_allocated': 1.2097643817579995,\n",
       "  'avg_lump_sum_beats_avg': 0.6243358129649309,\n",
       "  'avg_ROIC': 1.7811007224070659,\n",
       "  'avg_sharpe': 0.13159280821669578,\n",
       "  'avg_DD': 0.3944535628408029,\n",
       "  'avg_DaR_DD_abs_95': 0.7353129570885923,\n",
       "  'avg_outperformance_DV100': -136.00313500333775,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.7283028396520308},\n",
       " {'frequency': 'M',\n",
       "  'allocation_periods': 12,\n",
       "  'upfront_percent': 0.25,\n",
       "  'capital': 10000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-02-25 00:00:00'),\n",
       "  'risk_free_rate': 0.05,\n",
       "  'number_of_allocations': 1882,\n",
       "  'avg_BTC_allocated': 1.3173292143758226,\n",
       "  'avg_lump_sum_beats_avg': 0.6243358129649309,\n",
       "  'avg_ROIC': 2.0283791496858616,\n",
       "  'avg_sharpe': 0.15068137052318714,\n",
       "  'avg_DD': 0.3942755771091406,\n",
       "  'avg_DaR_DD_abs_95': 0.7368507367680528,\n",
       "  'avg_outperformance_DV100': -111.27529227545818,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.7283028396520308},\n",
       " {'frequency': 'M',\n",
       "  'allocation_periods': 12,\n",
       "  'upfront_percent': 1,\n",
       "  'capital': 10000,\n",
       "  'start_date': Timestamp('2017-01-01 00:00:00'),\n",
       "  'end_date': Timestamp('2023-02-25 00:00:00'),\n",
       "  'risk_free_rate': 0.05,\n",
       "  'number_of_allocations': 1882,\n",
       "  'avg_BTC_allocated': 1.8013709611560265,\n",
       "  'avg_lump_sum_beats_avg': 0.0,\n",
       "  'avg_ROIC': 3.1411320724404432,\n",
       "  'avg_sharpe': 0.19872620179488037,\n",
       "  'avg_DD': 0.3916417584887475,\n",
       "  'avg_DaR_DD_abs_95': 0.7426384876734902,\n",
       "  'avg_outperformance_DV100': 7.173385748906432e-16,\n",
       "  'avg_BTC_bought_ls_over_dca': 1.0}]"
      ]
     },
     "execution_count": 355,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim_results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 356,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>frequency</th>\n",
       "      <th>allocation_periods</th>\n",
       "      <th>upfront_percent</th>\n",
       "      <th>capital</th>\n",
       "      <th>start_date</th>\n",
       "      <th>end_date</th>\n",
       "      <th>risk_free_rate</th>\n",
       "      <th>number_of_allocations</th>\n",
       "      <th>avg_BTC_allocated</th>\n",
       "      <th>avg_lump_sum_beats_avg</th>\n",
       "      <th>avg_ROIC</th>\n",
       "      <th>avg_sharpe</th>\n",
       "      <th>avg_DD</th>\n",
       "      <th>avg_DaR_DD_abs_95</th>\n",
       "      <th>avg_outperformance_DV100</th>\n",
       "      <th>avg_BTC_bought_ls_over_dca</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>D</td>\n",
       "      <td>10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2237</td>\n",
       "      <td>1.57</td>\n",
       "      <td>0.56</td>\n",
       "      <td>2.60</td>\n",
       "      <td>0.38</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.67</td>\n",
       "      <td>-4.46</td>\n",
       "      <td>1.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>D</td>\n",
       "      <td>10</td>\n",
       "      <td>0.25</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2237</td>\n",
       "      <td>1.57</td>\n",
       "      <td>0.56</td>\n",
       "      <td>2.61</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.67</td>\n",
       "      <td>-3.72</td>\n",
       "      <td>1.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>D</td>\n",
       "      <td>10</td>\n",
       "      <td>1.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2237</td>\n",
       "      <td>1.58</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.64</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>D</td>\n",
       "      <td>15</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2232</td>\n",
       "      <td>1.56</td>\n",
       "      <td>0.56</td>\n",
       "      <td>2.58</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.67</td>\n",
       "      <td>-7.23</td>\n",
       "      <td>1.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>D</td>\n",
       "      <td>15</td>\n",
       "      <td>0.25</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2232</td>\n",
       "      <td>1.56</td>\n",
       "      <td>0.56</td>\n",
       "      <td>2.59</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.67</td>\n",
       "      <td>-5.81</td>\n",
       "      <td>1.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>D</td>\n",
       "      <td>15</td>\n",
       "      <td>1.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2232</td>\n",
       "      <td>1.59</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.65</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>D</td>\n",
       "      <td>30</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2217</td>\n",
       "      <td>1.53</td>\n",
       "      <td>0.55</td>\n",
       "      <td>2.51</td>\n",
       "      <td>0.32</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.67</td>\n",
       "      <td>-15.82</td>\n",
       "      <td>1.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>D</td>\n",
       "      <td>30</td>\n",
       "      <td>0.25</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2217</td>\n",
       "      <td>1.54</td>\n",
       "      <td>0.55</td>\n",
       "      <td>2.54</td>\n",
       "      <td>0.33</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.68</td>\n",
       "      <td>-12.27</td>\n",
       "      <td>1.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>D</td>\n",
       "      <td>30</td>\n",
       "      <td>1.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2217</td>\n",
       "      <td>1.60</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.67</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>W</td>\n",
       "      <td>4</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2219</td>\n",
       "      <td>1.54</td>\n",
       "      <td>0.55</td>\n",
       "      <td>2.55</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.68</td>\n",
       "      <td>-11.40</td>\n",
       "      <td>1.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>W</td>\n",
       "      <td>4</td>\n",
       "      <td>0.25</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2219</td>\n",
       "      <td>1.54</td>\n",
       "      <td>0.55</td>\n",
       "      <td>2.55</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.68</td>\n",
       "      <td>-11.40</td>\n",
       "      <td>1.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>W</td>\n",
       "      <td>4</td>\n",
       "      <td>1.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2219</td>\n",
       "      <td>1.59</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.66</td>\n",
       "      <td>0.43</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>W</td>\n",
       "      <td>8</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2191</td>\n",
       "      <td>1.49</td>\n",
       "      <td>0.57</td>\n",
       "      <td>2.43</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.68</td>\n",
       "      <td>-26.54</td>\n",
       "      <td>1.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>W</td>\n",
       "      <td>8</td>\n",
       "      <td>0.25</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2191</td>\n",
       "      <td>1.51</td>\n",
       "      <td>0.57</td>\n",
       "      <td>2.47</td>\n",
       "      <td>0.28</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.68</td>\n",
       "      <td>-22.75</td>\n",
       "      <td>1.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>W</td>\n",
       "      <td>8</td>\n",
       "      <td>1.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2191</td>\n",
       "      <td>1.61</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.70</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.69</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>M</td>\n",
       "      <td>6</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2063</td>\n",
       "      <td>1.35</td>\n",
       "      <td>0.55</td>\n",
       "      <td>2.10</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.70</td>\n",
       "      <td>-75.21</td>\n",
       "      <td>1.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>M</td>\n",
       "      <td>6</td>\n",
       "      <td>0.25</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2063</td>\n",
       "      <td>1.38</td>\n",
       "      <td>0.55</td>\n",
       "      <td>2.17</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.71</td>\n",
       "      <td>-67.69</td>\n",
       "      <td>1.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>M</td>\n",
       "      <td>6</td>\n",
       "      <td>1.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>2063</td>\n",
       "      <td>1.67</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2.85</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>M</td>\n",
       "      <td>12</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>1882</td>\n",
       "      <td>1.21</td>\n",
       "      <td>0.62</td>\n",
       "      <td>1.78</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.74</td>\n",
       "      <td>-136.00</td>\n",
       "      <td>1.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>M</td>\n",
       "      <td>12</td>\n",
       "      <td>0.25</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>1882</td>\n",
       "      <td>1.32</td>\n",
       "      <td>0.62</td>\n",
       "      <td>2.03</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.74</td>\n",
       "      <td>-111.28</td>\n",
       "      <td>1.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>M</td>\n",
       "      <td>12</td>\n",
       "      <td>1.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>1882</td>\n",
       "      <td>1.80</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3.14</td>\n",
       "      <td>0.20</td>\n",
       "      <td>0.39</td>\n",
       "      <td>0.74</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   frequency  allocation_periods  upfront_percent  capital start_date  \\\n",
       "0          D                  10             0.00    10000 2017-01-01   \n",
       "1          D                  10             0.25    10000 2017-01-01   \n",
       "2          D                  10             1.00    10000 2017-01-01   \n",
       "3          D                  15             0.00    10000 2017-01-01   \n",
       "4          D                  15             0.25    10000 2017-01-01   \n",
       "5          D                  15             1.00    10000 2017-01-01   \n",
       "6          D                  30             0.00    10000 2017-01-01   \n",
       "7          D                  30             0.25    10000 2017-01-01   \n",
       "8          D                  30             1.00    10000 2017-01-01   \n",
       "9          W                   4             0.00    10000 2017-01-01   \n",
       "10         W                   4             0.25    10000 2017-01-01   \n",
       "11         W                   4             1.00    10000 2017-01-01   \n",
       "12         W                   8             0.00    10000 2017-01-01   \n",
       "13         W                   8             0.25    10000 2017-01-01   \n",
       "14         W                   8             1.00    10000 2017-01-01   \n",
       "15         M                   6             0.00    10000 2017-01-01   \n",
       "16         M                   6             0.25    10000 2017-01-01   \n",
       "17         M                   6             1.00    10000 2017-01-01   \n",
       "18         M                  12             0.00    10000 2017-01-01   \n",
       "19         M                  12             0.25    10000 2017-01-01   \n",
       "20         M                  12             1.00    10000 2017-01-01   \n",
       "\n",
       "     end_date  risk_free_rate  number_of_allocations  avg_BTC_allocated  \\\n",
       "0  2023-02-25            0.05                   2237               1.57   \n",
       "1  2023-02-25            0.05                   2237               1.57   \n",
       "2  2023-02-25            0.05                   2237               1.58   \n",
       "3  2023-02-25            0.05                   2232               1.56   \n",
       "4  2023-02-25            0.05                   2232               1.56   \n",
       "5  2023-02-25            0.05                   2232               1.59   \n",
       "6  2023-02-25            0.05                   2217               1.53   \n",
       "7  2023-02-25            0.05                   2217               1.54   \n",
       "8  2023-02-25            0.05                   2217               1.60   \n",
       "9  2023-02-25            0.05                   2219               1.54   \n",
       "10 2023-02-25            0.05                   2219               1.54   \n",
       "11 2023-02-25            0.05                   2219               1.59   \n",
       "12 2023-02-25            0.05                   2191               1.49   \n",
       "13 2023-02-25            0.05                   2191               1.51   \n",
       "14 2023-02-25            0.05                   2191               1.61   \n",
       "15 2023-02-25            0.05                   2063               1.35   \n",
       "16 2023-02-25            0.05                   2063               1.38   \n",
       "17 2023-02-25            0.05                   2063               1.67   \n",
       "18 2023-02-25            0.05                   1882               1.21   \n",
       "19 2023-02-25            0.05                   1882               1.32   \n",
       "20 2023-02-25            0.05                   1882               1.80   \n",
       "\n",
       "    avg_lump_sum_beats_avg  avg_ROIC  avg_sharpe  avg_DD  avg_DaR_DD_abs_95  \\\n",
       "0                     0.56      2.60        0.38    0.36               0.67   \n",
       "1                     0.56      2.61        0.39    0.36               0.67   \n",
       "2                     0.00      2.64        0.43    0.36               0.67   \n",
       "3                     0.56      2.58        0.36    0.36               0.67   \n",
       "4                     0.56      2.59        0.37    0.36               0.67   \n",
       "5                     0.00      2.65        0.43    0.36               0.68   \n",
       "6                     0.55      2.51        0.32    0.36               0.67   \n",
       "7                     0.55      2.54        0.33    0.36               0.68   \n",
       "8                     0.00      2.67        0.43    0.36               0.68   \n",
       "9                     0.55      2.55        0.34    0.36               0.68   \n",
       "10                    0.55      2.55        0.34    0.36               0.68   \n",
       "11                    0.00      2.66        0.43    0.36               0.68   \n",
       "12                    0.57      2.43        0.28    0.36               0.68   \n",
       "13                    0.57      2.47        0.28    0.36               0.68   \n",
       "14                    0.00      2.70        0.34    0.37               0.69   \n",
       "15                    0.55      2.10        0.15    0.37               0.70   \n",
       "16                    0.55      2.17        0.15    0.37               0.71   \n",
       "17                    0.00      2.85        0.14    0.39               0.72   \n",
       "18                    0.62      1.78        0.13    0.39               0.74   \n",
       "19                    0.62      2.03        0.15    0.39               0.74   \n",
       "20                    0.00      3.14        0.20    0.39               0.74   \n",
       "\n",
       "    avg_outperformance_DV100  avg_BTC_bought_ls_over_dca  \n",
       "0                      -4.46                        1.01  \n",
       "1                      -3.72                        1.01  \n",
       "2                       0.00                        1.00  \n",
       "3                      -7.23                        1.02  \n",
       "4                      -5.81                        1.02  \n",
       "5                       0.00                        1.00  \n",
       "6                     -15.82                        1.04  \n",
       "7                     -12.27                        1.04  \n",
       "8                       0.00                        1.00  \n",
       "9                     -11.40                        1.03  \n",
       "10                    -11.40                        1.03  \n",
       "11                      0.00                        1.00  \n",
       "12                    -26.54                        1.06  \n",
       "13                    -22.75                        1.06  \n",
       "14                      0.00                        1.00  \n",
       "15                    -75.21                        1.25  \n",
       "16                    -67.69                        1.25  \n",
       "17                      0.00                        1.00  \n",
       "18                   -136.00                        1.73  \n",
       "19                   -111.28                        1.73  \n",
       "20                      0.00                        1.00  "
      ]
     },
     "execution_count": 356,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 357,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>frequency</th>\n",
       "      <th>allocation_periods</th>\n",
       "      <th>upfront_percent</th>\n",
       "      <th>capital</th>\n",
       "      <th>start_date</th>\n",
       "      <th>end_date</th>\n",
       "      <th>risk_free_rate</th>\n",
       "      <th>capital allocated</th>\n",
       "      <th>BTC allocated</th>\n",
       "      <th>...</th>\n",
       "      <th>weighted_avg_cost</th>\n",
       "      <th>avg_buy_price</th>\n",
       "      <th>max_buy_price</th>\n",
       "      <th>min_buy_price</th>\n",
       "      <th>first_buy_price</th>\n",
       "      <th>lump_sum_beats_avg</th>\n",
       "      <th>BTC_bought_with_dca</th>\n",
       "      <th>BTC_bought_with_ls</th>\n",
       "      <th>BTC_bought_ls_over_dca</th>\n",
       "      <th>type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>D</td>\n",
       "      <td>10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>10,000.00</td>\n",
       "      <td>10.43</td>\n",
       "      <td>...</td>\n",
       "      <td>958.98</td>\n",
       "      <td>965.06</td>\n",
       "      <td>1,135.41</td>\n",
       "      <td>886.16</td>\n",
       "      <td>995.44</td>\n",
       "      <td>False</td>\n",
       "      <td>10.36</td>\n",
       "      <td>10.05</td>\n",
       "      <td>0.97</td>\n",
       "      <td>D_10_0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>D</td>\n",
       "      <td>10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-02</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>10,000.00</td>\n",
       "      <td>10.70</td>\n",
       "      <td>...</td>\n",
       "      <td>934.90</td>\n",
       "      <td>944.06</td>\n",
       "      <td>1,135.41</td>\n",
       "      <td>785.43</td>\n",
       "      <td>1,017.05</td>\n",
       "      <td>False</td>\n",
       "      <td>10.59</td>\n",
       "      <td>9.83</td>\n",
       "      <td>0.93</td>\n",
       "      <td>D_10_0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>D</td>\n",
       "      <td>10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-03</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>10,000.00</td>\n",
       "      <td>10.95</td>\n",
       "      <td>...</td>\n",
       "      <td>913.45</td>\n",
       "      <td>923.36</td>\n",
       "      <td>1,135.41</td>\n",
       "      <td>785.43</td>\n",
       "      <td>1,033.30</td>\n",
       "      <td>False</td>\n",
       "      <td>10.83</td>\n",
       "      <td>9.68</td>\n",
       "      <td>0.89</td>\n",
       "      <td>D_10_0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>D</td>\n",
       "      <td>10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-04</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>10,000.00</td>\n",
       "      <td>11.19</td>\n",
       "      <td>...</td>\n",
       "      <td>893.49</td>\n",
       "      <td>902.52</td>\n",
       "      <td>1,135.41</td>\n",
       "      <td>785.43</td>\n",
       "      <td>1,135.41</td>\n",
       "      <td>False</td>\n",
       "      <td>11.08</td>\n",
       "      <td>8.81</td>\n",
       "      <td>0.79</td>\n",
       "      <td>D_10_0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>D</td>\n",
       "      <td>10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2017-01-05</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>10,000.00</td>\n",
       "      <td>11.53</td>\n",
       "      <td>...</td>\n",
       "      <td>867.19</td>\n",
       "      <td>870.94</td>\n",
       "      <td>989.35</td>\n",
       "      <td>785.43</td>\n",
       "      <td>989.35</td>\n",
       "      <td>False</td>\n",
       "      <td>11.48</td>\n",
       "      <td>10.11</td>\n",
       "      <td>0.88</td>\n",
       "      <td>D_10_0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45118</th>\n",
       "      <td>1877</td>\n",
       "      <td>M</td>\n",
       "      <td>12</td>\n",
       "      <td>1.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2022-02-21</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>10,000.00</td>\n",
       "      <td>0.27</td>\n",
       "      <td>...</td>\n",
       "      <td>37,037.39</td>\n",
       "      <td>37,037.39</td>\n",
       "      <td>37,037.39</td>\n",
       "      <td>37,037.39</td>\n",
       "      <td>37,037.39</td>\n",
       "      <td>False</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.27</td>\n",
       "      <td>1.00</td>\n",
       "      <td>M_12_1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45119</th>\n",
       "      <td>1878</td>\n",
       "      <td>M</td>\n",
       "      <td>12</td>\n",
       "      <td>1.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2022-02-22</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>10,000.00</td>\n",
       "      <td>0.26</td>\n",
       "      <td>...</td>\n",
       "      <td>38,267.75</td>\n",
       "      <td>38,267.75</td>\n",
       "      <td>38,267.75</td>\n",
       "      <td>38,267.75</td>\n",
       "      <td>38,267.75</td>\n",
       "      <td>False</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.26</td>\n",
       "      <td>1.00</td>\n",
       "      <td>M_12_1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45120</th>\n",
       "      <td>1879</td>\n",
       "      <td>M</td>\n",
       "      <td>12</td>\n",
       "      <td>1.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2022-02-23</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>10,000.00</td>\n",
       "      <td>0.27</td>\n",
       "      <td>...</td>\n",
       "      <td>37,270.85</td>\n",
       "      <td>37,270.85</td>\n",
       "      <td>37,270.85</td>\n",
       "      <td>37,270.85</td>\n",
       "      <td>37,270.85</td>\n",
       "      <td>False</td>\n",
       "      <td>0.27</td>\n",
       "      <td>0.27</td>\n",
       "      <td>1.00</td>\n",
       "      <td>M_12_1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45121</th>\n",
       "      <td>1880</td>\n",
       "      <td>M</td>\n",
       "      <td>12</td>\n",
       "      <td>1.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2022-02-24</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>10,000.00</td>\n",
       "      <td>0.26</td>\n",
       "      <td>...</td>\n",
       "      <td>38,353.62</td>\n",
       "      <td>38,353.62</td>\n",
       "      <td>38,353.62</td>\n",
       "      <td>38,353.62</td>\n",
       "      <td>38,353.62</td>\n",
       "      <td>False</td>\n",
       "      <td>0.26</td>\n",
       "      <td>0.26</td>\n",
       "      <td>1.00</td>\n",
       "      <td>M_12_1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45122</th>\n",
       "      <td>1881</td>\n",
       "      <td>M</td>\n",
       "      <td>12</td>\n",
       "      <td>1.00</td>\n",
       "      <td>10000</td>\n",
       "      <td>2022-02-25</td>\n",
       "      <td>2023-02-25</td>\n",
       "      <td>0.05</td>\n",
       "      <td>10,000.00</td>\n",
       "      <td>0.25</td>\n",
       "      <td>...</td>\n",
       "      <td>39,239.77</td>\n",
       "      <td>39,239.77</td>\n",
       "      <td>39,239.77</td>\n",
       "      <td>39,239.77</td>\n",
       "      <td>39,239.77</td>\n",
       "      <td>False</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.25</td>\n",
       "      <td>1.00</td>\n",
       "      <td>M_12_1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>45123 rows × 39 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       index frequency  allocation_periods  upfront_percent  capital  \\\n",
       "0          0         D                  10             0.00    10000   \n",
       "1          1         D                  10             0.00    10000   \n",
       "2          2         D                  10             0.00    10000   \n",
       "3          3         D                  10             0.00    10000   \n",
       "4          4         D                  10             0.00    10000   \n",
       "...      ...       ...                 ...              ...      ...   \n",
       "45118   1877         M                  12             1.00    10000   \n",
       "45119   1878         M                  12             1.00    10000   \n",
       "45120   1879         M                  12             1.00    10000   \n",
       "45121   1880         M                  12             1.00    10000   \n",
       "45122   1881         M                  12             1.00    10000   \n",
       "\n",
       "      start_date   end_date  risk_free_rate  capital allocated  BTC allocated  \\\n",
       "0     2017-01-01 2023-02-25            0.05          10,000.00          10.43   \n",
       "1     2017-01-02 2023-02-25            0.05          10,000.00          10.70   \n",
       "2     2017-01-03 2023-02-25            0.05          10,000.00          10.95   \n",
       "3     2017-01-04 2023-02-25            0.05          10,000.00          11.19   \n",
       "4     2017-01-05 2023-02-25            0.05          10,000.00          11.53   \n",
       "...          ...        ...             ...                ...            ...   \n",
       "45118 2022-02-21 2023-02-25            0.05          10,000.00           0.27   \n",
       "45119 2022-02-22 2023-02-25            0.05          10,000.00           0.26   \n",
       "45120 2022-02-23 2023-02-25            0.05          10,000.00           0.27   \n",
       "45121 2022-02-24 2023-02-25            0.05          10,000.00           0.26   \n",
       "45122 2022-02-25 2023-02-25            0.05          10,000.00           0.25   \n",
       "\n",
       "       ...  weighted_avg_cost  avg_buy_price  max_buy_price  min_buy_price  \\\n",
       "0      ...             958.98         965.06       1,135.41         886.16   \n",
       "1      ...             934.90         944.06       1,135.41         785.43   \n",
       "2      ...             913.45         923.36       1,135.41         785.43   \n",
       "3      ...             893.49         902.52       1,135.41         785.43   \n",
       "4      ...             867.19         870.94         989.35         785.43   \n",
       "...    ...                ...            ...            ...            ...   \n",
       "45118  ...          37,037.39      37,037.39      37,037.39      37,037.39   \n",
       "45119  ...          38,267.75      38,267.75      38,267.75      38,267.75   \n",
       "45120  ...          37,270.85      37,270.85      37,270.85      37,270.85   \n",
       "45121  ...          38,353.62      38,353.62      38,353.62      38,353.62   \n",
       "45122  ...          39,239.77      39,239.77      39,239.77      39,239.77   \n",
       "\n",
       "       first_buy_price  lump_sum_beats_avg  BTC_bought_with_dca  \\\n",
       "0               995.44               False                10.36   \n",
       "1             1,017.05               False                10.59   \n",
       "2             1,033.30               False                10.83   \n",
       "3             1,135.41               False                11.08   \n",
       "4               989.35               False                11.48   \n",
       "...                ...                 ...                  ...   \n",
       "45118        37,037.39               False                 0.27   \n",
       "45119        38,267.75               False                 0.26   \n",
       "45120        37,270.85               False                 0.27   \n",
       "45121        38,353.62               False                 0.26   \n",
       "45122        39,239.77               False                 0.25   \n",
       "\n",
       "       BTC_bought_with_ls  BTC_bought_ls_over_dca      type  \n",
       "0                   10.05                    0.97  D_10_0.0  \n",
       "1                    9.83                    0.93  D_10_0.0  \n",
       "2                    9.68                    0.89  D_10_0.0  \n",
       "3                    8.81                    0.79  D_10_0.0  \n",
       "4                   10.11                    0.88  D_10_0.0  \n",
       "...                   ...                     ...       ...  \n",
       "45118                0.27                    1.00  M_12_1.0  \n",
       "45119                0.26                    1.00  M_12_1.0  \n",
       "45120                0.27                    1.00  M_12_1.0  \n",
       "45121                0.26                    1.00  M_12_1.0  \n",
       "45122                0.25                    1.00  M_12_1.0  \n",
       "\n",
       "[45123 rows x 39 columns]"
      ]
     },
     "execution_count": 357,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_df = full_df.reset_index()\n",
    "full_df['type'] = full_df['frequency'] + '_' + full_df['allocation_periods'].astype(str) + '_' + full_df['upfront_percent'].astype(str) \n",
    "full_df "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 358,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['index', 'frequency', 'allocation_periods', 'upfront_percent',\n",
       "       'capital', 'start_date', 'end_date', 'risk_free_rate',\n",
       "       'capital allocated', 'BTC allocated', 'max portfolio value',\n",
       "       'final portfolio value', 'ROIC', 'MOIC', 'number_points',\n",
       "       'volatility_daily', 'annualization_factor', 'volatility_annual',\n",
       "       'return_annual', 'sharpe_ratio', 'hist_VaR_95', 'max_DD_abs',\n",
       "       'avg_DD_abs', 'DaR_DD_abs_95', 'BTC_initial', 'BTC_final', 'BTC_MOIC',\n",
       "       'BTC_period', 'outperformance_DV100', 'weighted_avg_cost',\n",
       "       'avg_buy_price', 'max_buy_price', 'min_buy_price', 'first_buy_price',\n",
       "       'lump_sum_beats_avg', 'BTC_bought_with_dca', 'BTC_bought_with_ls',\n",
       "       'BTC_bought_ls_over_dca', 'type'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 358,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 359,
   "metadata": {},
   "outputs": [],
   "source": [
    "sim_df.to_excel(\"output.xlsx\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 360,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.098773681021606\n",
      "2017-01-01 00:00:00\n"
     ]
    }
   ],
   "source": [
    "# Average Outperformance LS over DCA (all data)\n",
    "print(full_df['BTC_bought_ls_over_dca'].mean())\n",
    "print(full_df['start_date'].min())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 360,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x400 with 0 Axes>"
      ]
     },
     "execution_count": 361,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x400 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# MatPlotLib settings\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import seaborn as sns\n",
    "from cycler import cycler\n",
    "# Swan Colors\n",
    "swan_colors = ['#31597F', '#7B96B0', '#C3D9E9', '#DAE1E8']\n",
    "mpl.rcParams['lines.color'] = '#31597F'\n",
    "mpl.rcParams['text.color'] = '#31597F'\n",
    "mpl.rcParams['axes.prop_cycle'] = cycler(color=swan_colors)\n",
    "mpl.rcParams['lines.linewidth'] = 1\n",
    "sns.set_style('darkgrid') # darkgrid, white grid, dark, white and ticks\n",
    "sns.color_palette('pastel')\n",
    "plt.rc('axes', titlesize=12)\n",
    "plt.rc('axes', labelsize=8)   \n",
    "plt.rc('xtick', labelsize=8, color='#00305E')  \n",
    "plt.rc('ytick', labelsize=8, color='#00305E')    \n",
    "plt.rc('legend', fontsize=12)\n",
    "plt.rc('font', size=8)          \n",
    "plt.figure(figsize=(10, 4), tight_layout=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 388,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Distribution of Over / underperformance\n",
    "cust_bins = range(200, 2000, 10)\n",
    "cust_bins = [x / 1000 for x in cust_bins]\n",
    "plt.figure(figsize=(10, 4), tight_layout=True)\n",
    "\n",
    "# Remove 1.00 to clean dataset\n",
    "t_df = full_df.loc[full_df['BTC_bought_ls_over_dca'] != 1]\n",
    "\n",
    "# Filter dates\n",
    "start_date = pd.to_datetime('2021-01-01', format='%Y-%m-%d')\n",
    "# end_date = pd.to_datetime('2023-01-01', format='%Y-%m-%d')\n",
    "t_df = t_df.loc[full_df['start_date'] >= start_date]\n",
    "\n",
    "\n",
    "chart = t_df['BTC_bought_ls_over_dca'].hist(bins=cust_bins, linewidth=1)\n",
    "title = 'Outperformance of Lump Sum over Dollar Cost Average'\n",
    "subtitle = 'Outperformance Multiple (> 1.00 = LumpSum outperforms)'\n",
    "plt.title(title)\n",
    "plt.xlabel(subtitle)\n",
    "plt.ylabel('Count')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 362,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/dv/t5p9gs7d27dbtm0x8l0kvf600000gq/T/ipykernel_30082/2637017228.py:8: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  barplot = t_df.groupby(['type'], as_index=False).mean()[['BTC_bought_ls_over_dca', 'type']]\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 4), tight_layout=True)\n",
    "\n",
    "customPalette = sns.color_palette(swan_colors, 1)\n",
    "\n",
    "# Remove 1.00 to clean dataset\n",
    "t_df = full_df.loc[full_df['BTC_bought_ls_over_dca'] != 1]\n",
    "\n",
    "barplot = t_df.groupby(['type'], as_index=False).mean()[['BTC_bought_ls_over_dca', 'type']]\n",
    "ax = sns.barplot(x=barplot['type'], y=barplot['BTC_bought_ls_over_dca'], palette=customPalette)\n",
    "\n",
    "ax.set(title='DCA Strategies outperformance compared to lumpsum', xlabel='Type', ylabel='Outperformance')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 391,
   "metadata": {},
   "outputs": [],
   "source": [
    "t_df.to_csv('DCA.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 363,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/dv/t5p9gs7d27dbtm0x8l0kvf600000gq/T/ipykernel_30082/1813038717.py:8: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  barplot = t_df.groupby(['type'], as_index=False).mean()[['BTC_bought_ls_over_dca', 'type']]\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 4), tight_layout=True)\n",
    "\n",
    "customPalette = sns.color_palette(swan_colors, 1)\n",
    "\n",
    "# Remove 1.00 to clean dataset\n",
    "t_df = full_df.loc[full_df['BTC_bought_ls_over_dca'] != 1]\n",
    "\n",
    "barplot = t_df.groupby(['type'], as_index=False).mean()[['BTC_bought_ls_over_dca', 'type']]\n",
    "daily_plot = barplot[barplot['type'].str.contains(\"M\")]\n",
    "ax = sns.barplot(x=daily_plot['type'], y=daily_plot['BTC_bought_ls_over_dca'], palette=customPalette)\n",
    "\n",
    "ax.set(title='DCA Strategies outperformance compared to lumpsum', xlabel='Type', ylabel='Outperformance')\n",
    "ax.set(ylim=(1.20, 1.80))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 364,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['D_10_0.0', 'D_10_0.25', 'D_10_1.0', 'D_15_0.0', 'D_15_0.25',\n",
       "       'D_15_1.0', 'D_30_0.0', 'D_30_0.25', 'D_30_1.0', 'W_4_0.0',\n",
       "       'W_4_0.25', 'W_4_1.0', 'W_8_0.0', 'W_8_0.25', 'W_8_1.0', 'M_6_0.0',\n",
       "       'M_6_0.25', 'M_6_1.0', 'M_12_0.0', 'M_12_0.25', 'M_12_1.0'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 364,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_df['type'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 380,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tdf  = full_df[~full_df['type'].str.contains(\"_1.0\")]\n",
    "tdf['diff'] = tdf['BTC_bought_with_dca'] - tdf['BTC_bought_with_ls']\n",
    "plt.figure(figsize=(8, 8), tight_layout=True)\n",
    "ax = sns.scatterplot(x=tdf['type'], y=tdf['diff'],\n",
    "                hue=tdf['diff'],\n",
    "                sizes=(10,700),\n",
    "                palette='Spectral')\n",
    "ax.set(title='DCA Strategies difference in BTC bought \\n compared to lumpsum \\n ($10,000 investment)', \n",
    "       xlabel='Type', ylabel='Outperformance')\n",
    "plt.legend([],[], frameon=False)\n",
    "plt.xticks(rotation=90)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 407,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tdf  = full_df[~full_df['type'].str.contains(\"_1.0\")]\n",
    "tdf['diff'] = tdf['BTC_bought_with_dca'] - tdf['BTC_bought_with_ls']\n",
    "plt.figure(figsize=(8, 5), tight_layout=True)\n",
    "ax = sns.scatterplot(x=tdf['type'], y=tdf['DaR_DD_abs_95'],\n",
    "                sizes=(10,500), color='#0077CC')\n",
    "ax.set(title='DCA Strategies difference in BTC bought \\n compared to lumpsum \\n ($10,000 investment)', \n",
    "       xlabel='Type', ylabel='Drawdown at Risk (95% CI)')\n",
    "ax.set_facecolor('white')\n",
    "plt.grid(c='#DAE1E8', linestyle='--')\n",
    "plt.legend([],[], frameon=False)\n",
    "plt.xticks(rotation=90)\n",
    "plt.savefig('dd_highres.eps', format='eps')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 408,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/dv/t5p9gs7d27dbtm0x8l0kvf600000gq/T/ipykernel_30082/3838876353.py:4: UserWarning: Ignoring `palette` because no `hue` variable has been assigned.\n",
      "  ax = sns.scatterplot(x=tdf['type'], y=tdf['volatility_annual'],\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tdf  = full_df[~full_df['type'].str.contains(\"_1.0\")]\n",
    "tdf['diff'] = tdf['BTC_bought_with_dca'] - tdf['BTC_bought_with_ls']\n",
    "plt.figure(figsize=(8, 5), tight_layout=True)\n",
    "ax = sns.scatterplot(x=tdf['type'], y=tdf['volatility_annual'],\n",
    "                color='#0077CC',\n",
    "                sizes=(10,500),\n",
    "                palette='Spectral')\n",
    "ax.set(title='DCA Strategies difference in BTC bought \\n compared to lumpsum \\n ($10,000 investment)', \n",
    "       xlabel='Type', ylabel='Volatility (annualized)')\n",
    "ax.set_facecolor('white')\n",
    "plt.grid(c='#DAE1E8', linestyle='--')\n",
    "plt.legend([],[], frameon=False)\n",
    "plt.xticks(rotation=90)\n",
    "plt.savefig('vol_highres.eps', format='eps')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 387,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tdf  = full_df[~full_df['type'].str.contains(\"_1.0\")]\n",
    "tdf['diff'] = tdf['BTC_bought_with_dca'] - tdf['BTC_bought_with_ls']\n",
    "tdf['year'] = tdf['start_date'].dt.year\n",
    "tdf = tdf[tdf['year'] > 2020]\n",
    "plt.figure(figsize=(8, 8), tight_layout=True)\n",
    "ax = sns.scatterplot(x=tdf['year'], y=tdf['diff'],\n",
    "                hue=tdf['diff'],\n",
    "                sizes=(10,700),\n",
    "                palette='Spectral')\n",
    "ax.set(title='DCA Strategies difference in BTC bought \\n compared to lumpsum \\n ($10,000 investment)', \n",
    "       xlabel='Starting Year', ylabel='Outperformance')\n",
    "plt.legend([],[], frameon=False)\n",
    "plt.xticks(rotation=90)\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Analysis & Charts"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Optimization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 366,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Minimize DV100\n",
    "def optimize_allocation(allocation_periods):\n",
    "    # print(allocation_periods)\n",
    "    if allocation_periods < 2:\n",
    "        return 100000000000\n",
    "    opt_alloc = AllocationManager()\n",
    "    opt_alloc.capital = 100000\n",
    "    opt_alloc.allocation_periods = int(allocation_periods)\n",
    "    opt_alloc.frequency = 'D'\n",
    "    opt_alloc.start_date = pd.to_datetime('2018-01-01', format='%Y-%m-%d')\n",
    "    opt_alloc.upfront_percent = 0\n",
    "    opt_alloc.allocate_capital()\n",
    "    d, stats = run_through_time(opt_alloc)\n",
    "    # Maximize DV100\n",
    "    return (stats['outputs']['avg_outperformance_DV100'] * -1)\n",
    "\n",
    "from scipy.optimize import minimize_scalar\n",
    "\n",
    "# res = minimize_scalar(optimize_allocation, method='brent', options={'disp':1})\n",
    "# res.fun\n",
    "# res.x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 367,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Chart showing allocation periods results\n",
    "allocs = range(2, 180, 8)\n",
    "results_x = []\n",
    "results_y = []\n",
    "for alloc in allocs:\n",
    "    results_x.append(alloc)\n",
    "    results_y.append(optimize_allocation(alloc) * -1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 368,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<iframe style=\"border:0;outline:none;overflow:hidden\" srcdoc=\"&lt;!DOCTYPE html&gt; &lt;html lang=&quot;en&quot;&gt; &lt;head&gt; &lt;meta charset=&quot;utf-8&quot; /&gt; &lt;link href=&quot;https://www.highcharts.com/highslide/highslide.css&quot; rel=&quot;stylesheet&quot; /&gt; &lt;script type=&quot;text/javascript&quot; src=&quot;https://ajax.googleapis.com/ajax/libs/jquery/1.9.1/jquery.min.js&quot;&gt;&lt;/script&gt; &lt;script type=&quot;text/javascript&quot; src=&quot;https://code.highcharts.com/6/highcharts.js&quot;&gt;&lt;/script&gt; &lt;script type=&quot;text/javascript&quot; src=&quot;https://code.highcharts.com/6/highcharts-more.js&quot;&gt;&lt;/script&gt; &lt;script type=&quot;text/javascript&quot; src=&quot;https://code.highcharts.com/6/modules/heatmap.js&quot;&gt;&lt;/script&gt; &lt;script type=&quot;text/javascript&quot; src=&quot;https://code.highcharts.com/6/modules/exporting.js&quot;&gt;&lt;/script&gt; &lt;/head&gt; &lt;body style=&quot;margin:0;padding:0&quot;&gt; &lt;div id=&quot;container&quot; style=&quot;&quot;&gt;Loading....&lt;/div&gt; &lt;script&gt; $(function(){ Highcharts.setOptions({&quot;global&quot;: {}, &quot;lang&quot;: {}}); var option = {&quot;chart&quot;: {&quot;renderTo&quot;: &quot;container&quot;, &quot;backgroundColor&quot;: &quot;#FFFFFF&quot;, &quot;style&quot;: {&quot;fontFamily&quot;: &quot;Dosis, sans-serif&quot;}}, &quot;colors&quot;: [&quot;#2C6A3E&quot;, &quot;#09654E&quot;, &quot;#005F5A&quot;, &quot;#00585F&quot;, &quot;#1D505F&quot;, &quot;#2F4858&quot;], &quot;credits&quot;: {&quot;enabled&quot;: false}, &quot;drilldown&quot;: {}, &quot;exporting&quot;: {}, &quot;labels&quot;: {}, &quot;legend&quot;: {&quot;itemStyle&quot;: {&quot;fontWeight&quot;: &quot;bold&quot;, &quot;fontSize&quot;: &quot;10px&quot;}}, &quot;loading&quot;: {}, &quot;navigation&quot;: {}, &quot;pane&quot;: {}, &quot;plotOptions&quot;: {}, &quot;series&quot;: {}, &quot;subtitle&quot;: {&quot;text&quot;: &quot;&quot;}, &quot;title&quot;: {&quot;text&quot;: &quot;Outperformance of $100 invested lumpsum compared to cost average (since Jan, 2017)&quot;, &quot;style&quot;: {&quot;fontSize&quot;: &quot;12px&quot;, &quot;fontWeight&quot;: &quot;bold&quot;, &quot;textTransform&quot;: &quot;uppercase&quot;}}, &quot;tooltip&quot;: {&quot;borderWidth&quot;: 0, &quot;backgroundColor&quot;: &quot;rgba(219,219,216,0.8)&quot;, &quot;shadow&quot;: false, &quot;valueDecimals&quot;: 2}, &quot;xAxis&quot;: {&quot;gridLineWidth&quot;: 1, &quot;minPadding&quot;: 0, &quot;maxPadding&quot;: 0, &quot;startOnTick&quot;: true, &quot;endOnTick&quot;: true, &quot;labels&quot;: {&quot;style&quot;: {&quot;fontSize&quot;: &quot;10px&quot;}}, &quot;title&quot;: {&quot;text&quot;: &quot;DCA Allocation # of Weeks (0% upfront)&quot;}}, &quot;yAxis&quot;: {&quot;minorTickInterval&quot;: &quot;auto&quot;, &quot;title&quot;: {&quot;style&quot;: {&quot;textTransform&quot;: &quot;uppercase&quot;}, &quot;text&quot;: &quot;outperformance&quot;}, &quot;labels&quot;: {&quot;style&quot;: {&quot;fontSize&quot;: &quot;10px&quot;}}}}; var chart = new Highcharts.Chart(option); var data = [{&quot;data&quot;: [[2, -0.019109613668119668], [10, -0.13869481705004819], [18, -0.24698900011135946], [26, -0.42568271359441556], [34, -0.6293329855836078], [42, -0.8665199981798126], [50, -1.0617292708065253], [58, -1.2196230098999297], [66, -1.386997217933038], [74, -1.5705693875664568], [82, -1.7862734368760504], [90, -2.0104665593124076], [98, -2.2502347749050418], [106, -2.5316912875560313], [114, -2.896083437370947], [122, -3.2968940276254517], [130, -3.6666452734306016], [138, -4.028066781941781], [146, -4.407325708335978], [154, -4.785100930531307], [162, -5.173720079660705], [170, -5.62033956658282], [178, -6.052860396143711]], &quot;type&quot;: &quot;bar&quot;, &quot;name&quot;: &quot;outperf&quot;}, {&quot;data&quot;: [[2, -0.019109613668119668], [10, -0.13869481705004819], [18, -0.24698900011135946], [26, -0.42568271359441556], [34, -0.6293329855836078], [42, -0.8665199981798126], [50, -1.0617292708065253], [58, -1.2196230098999297], [66, -1.386997217933038], [74, -1.5705693875664568], [82, -1.7862734368760504], [90, -2.0104665593124076], [98, -2.2502347749050418], [106, -2.5316912875560313], [114, -2.896083437370947], [122, -3.2968940276254517], [130, -3.6666452734306016], [138, -4.028066781941781], [146, -4.407325708335978], [154, -4.785100930531307], [162, -5.173720079660705], [170, -5.62033956658282], [178, -6.052860396143711]], &quot;type&quot;: &quot;bar&quot;, &quot;dataLabels&quot;: {&quot;enabled&quot;: true, &quot;format&quot;: &quot;{point.properties.postal-code}&quot;}, &quot;name&quot;: &quot;outperf&quot;}]; var dataLen = data.length; for (var ix = 0; ix &lt; dataLen; ix++) { chart.addSeries(data[ix]); } }); &lt;/script&gt; &lt;/body&gt; &lt;/html&gt;\" height=520 width=820></iframe>"
      ],
      "text/plain": [
       "<highcharts.highcharts.highcharts.Highchart at 0x1a58fd2d0>"
      ]
     },
     "execution_count": 368,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_chart(results_x, results_y, f'DCA Allocation # of Weeks (0% upfront)', 'outperformance', 'bar', 'outperf', 'Outperformance of $100 invested lumpsum compared to cost average (since Jan, 2017)', dt=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".myenv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  },
  "vscode": {
   "interpreter": {
    "hash": "4e42ad074a612a92c728142607adbe16bb063d075b6a3eb41219fc2bed4f6659"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}