financial-planner.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Unit 5 - Financial Planning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initial imports\n",
    "import os\n",
    "import requests\n",
    "import pandas as pd\n",
    "from dotenv import load_dotenv\n",
    "import alpaca_trade_api as tradeapi\n",
    "from MCForecastTools import MCSimulation\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load .env enviroment variables\n",
    "load_dotenv()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Part 1 - Personal Finance Planner"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Collect Crypto Prices Using the `requests` Library"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set current amount of crypto assets\n",
    "my_btc = 1.2\n",
    "my_eth = 5.3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Crypto API URLs\n",
    "btc_url = \"https://api.alternative.me/v2/ticker/Bitcoin/?convert=CAD\"\n",
    "eth_url = \"https://api.alternative.me/v2/ticker/Ethereum/?convert=CAD\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The current value of your 1.2 BTC is $55182.00\n",
      "The current value of your 5.3 ETH is $3551.32\n"
     ]
    }
   ],
   "source": [
    "# Fetch current BTC price\n",
    "btc_response_data = requests.get(btc_url).json()\n",
    "btc_response_data\n",
    "\n",
    "# Fetch current ETH price\n",
    "eth_response_data = requests.get(eth_url).json()\n",
    "eth_response_data\n",
    "\n",
    "# Compute current value of my crypto\n",
    "btc_current_value = btc_response_data['data']['1']['quotes']['USD']['price']\n",
    "eth_current_value = eth_response_data['data']['1027']['quotes']['USD']['price']\n",
    "\n",
    "# Print current crypto wallet balance\n",
    "print(f\"The current value of your {my_btc} BTC is ${btc_current_value:0.2f}\") #0.2f prints two decimals on a float\n",
    "print(f\"The current value of your {my_eth} ETH is ${eth_current_value:0.2f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Collect Investments Data Using Alpaca: `SPY` (stocks) and `AGG` (bonds)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set current amount of shares\n",
    "my_agg = 200\n",
    "my_spy = 50"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set Alpaca API key and secret\n",
    "alpaca_api_key = os.getenv(\"ALPACA_API_KEY\")\n",
    "alpaca_secret_key = os.getenv(\"ALPACA_SECRET_KEY\")\n",
    "alpaca_end_point = os.getenv(\"ALPACA_END_POINT\")\n",
    "\n",
    "# Create the Alpaca API object\n",
    "alpaca = tradeapi.REST(\n",
    "    alpaca_api_key,\n",
    "    alpaca_secret_key,\n",
    "    api_version=\"v2\",\n",
    "    base_url= alpaca_end_point)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"5\" halign=\"left\">AGG</th>\n",
       "      <th colspan=\"5\" halign=\"left\">SPY</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</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>2021-10-08 00:00:00-04:00</th>\n",
       "      <td>114.31</td>\n",
       "      <td>114.35</td>\n",
       "      <td>114.07</td>\n",
       "      <td>114.12</td>\n",
       "      <td>4207570</td>\n",
       "      <td>439.48</td>\n",
       "      <td>439.89</td>\n",
       "      <td>437.19</td>\n",
       "      <td>437.82</td>\n",
       "      <td>57510090</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              AGG                                      SPY  \\\n",
       "                             open    high     low   close   volume    open   \n",
       "time                                                                         \n",
       "2021-10-08 00:00:00-04:00  114.31  114.35  114.07  114.12  4207570  439.48   \n",
       "\n",
       "                                                             \n",
       "                             high     low   close    volume  \n",
       "time                                                         \n",
       "2021-10-08 00:00:00-04:00  439.89  437.19  437.82  57510090  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Format current date as ISO format\n",
    "today = pd.Timestamp(\"2021-10-8\", tz=\"America/New_York\").isoformat()\n",
    "\n",
    "# Set the tickers\n",
    "tickers = [\"AGG\", \"SPY\"]\n",
    "\n",
    "# Set timeframe to '1D' for Alpaca API\n",
    "timeframe = \"1D\"\n",
    "\n",
    "# Get current closing prices for SPY and AGG\n",
    "df_portfolio = alpaca.get_barset(\n",
    "    tickers,\n",
    "    timeframe,\n",
    "    start = today,\n",
    "    end = today,\n",
    "    limit = 1000\n",
    ").df\n",
    "\n",
    "# Preview DataFrame\n",
    "df_portfolio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Current AGG closing price: $114.12\n",
      "Current SPY closing price: $437.82\n"
     ]
    }
   ],
   "source": [
    "# Pick AGG and SPY close prices\n",
    "agg_close_price = float(df_portfolio[\"AGG\"][\"close\"])\n",
    "spy_close_price = float(df_portfolio[\"SPY\"][\"close\"])\n",
    "\n",
    "# Print AGG and SPY close prices\n",
    "print(f\"Current AGG closing price: ${agg_close_price}\")\n",
    "print(f\"Current SPY closing price: ${spy_close_price}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The current value of your 50 SPY shares is $21891.00\n",
      "The current value of your 200 AGG shares is $22824.00\n"
     ]
    }
   ],
   "source": [
    "# Compute the current value of shares\n",
    "my_spy_value = my_spy * spy_close_price\n",
    "my_agg_value = my_agg * agg_close_price\n",
    "\n",
    "# Print current value of shares\n",
    "print(f\"The current value of your {my_spy} SPY shares is ${my_spy_value:0.2f}\")\n",
    "print(f\"The current value of your {my_agg} AGG shares is ${my_agg_value:0.2f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Savings Health Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>amount</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>asset</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>crypto</th>\n",
       "      <td>58733.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>shares</th>\n",
       "      <td>45648.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          amount\n",
       "asset           \n",
       "crypto  58733.32\n",
       "shares  45648.00"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Set monthly household income\n",
    "monthly_income = 12000\n",
    "\n",
    "# Consolidate financial assets data\n",
    "crypto_assets = btc_current_value + eth_current_value  #adding together all crypto\n",
    "stock_bond_assets = my_agg_value + my_agg_value #adding together all stocks and bonds\n",
    "\n",
    "value_data = {\n",
    "    'amount': [crypto_assets, stock_bond_assets],\n",
    "    'asset': [\"crypto\", \"shares\"]\n",
    "}\n",
    "\n",
    "# Create savings DataFrame\n",
    "df_savings = pd.DataFrame(value_data).set_index('asset')\n",
    "\n",
    "# Display savings DataFrame\n",
    "display(df_savings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot savings pie chart\n",
    "pie_chart = df_savings.plot.pie(y= 'amount', title=\"Savings Portfolio Composition\", figsize=(5,5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Congratulations! You have enough money in your emergency fund.\n"
     ]
    }
   ],
   "source": [
    "# Set ideal emergency fund\n",
    "emergency_fund = monthly_income * 3\n",
    "\n",
    "# Calculate total amount of savings\n",
    "total_savings = df_savings['amount'].sum()\n",
    "\n",
    "\n",
    "# Validate saving health\n",
    "\n",
    "#If total savings are greater than the emergency fund, display a message congratulating the person for having enough money in this fund.\n",
    "if total_savings > emergency_fund:\n",
    "    print(f\"Congratulations! You have enough money in your emergency fund.\")\n",
    "\n",
    "#If total savings are equal to the emergency fund, display a message congratulating the person on reaching this financial goal.\n",
    "elif total_savings == emergency_fund:\n",
    "    print(f\"You have reached your financial goal!\")\n",
    "\n",
    "#If total savings are less than the emergency fund, display a message showing how many dollars away the person is from reaching the goal.\n",
    "else:\n",
    "    print(f\"You're ${emergency_fund - total_savings:0.2f} away from achieving your financial goal. Keep saving!\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Part 2 - Retirement Planning\n",
    "\n",
    "### Monte Carlo Simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set start and end dates of five years back from today.\n",
    "# Sample results may vary from the solution based on the time frame chosen\n",
    "\n",
    "start_date1 = pd.Timestamp('2016-10-08', tz='America/New_York').isoformat()\n",
    "end_date1 = pd.Timestamp('2019-10-08', tz='America/New_York').isoformat()\n",
    "\n",
    "start_date2 = pd.Timestamp('2019-10-09', tz='America/New_York').isoformat()\n",
    "end_date2 = pd.Timestamp('2021-10-08', tz='America/New_York').isoformat()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"5\" halign=\"left\">AGG</th>\n",
       "      <th colspan=\"5\" halign=\"left\">SPY</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>open</th>\n",
       "      <th>volume</th>\n",
       "      <th>close</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>open</th>\n",
       "      <th>volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</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>2016-10-10 00:00:00-04:00</th>\n",
       "      <td>111.530</td>\n",
       "      <td>111.54</td>\n",
       "      <td>111.390</td>\n",
       "      <td>111.47</td>\n",
       "      <td>1115398.0</td>\n",
       "      <td>216.11</td>\n",
       "      <td>216.70</td>\n",
       "      <td>215.985</td>\n",
       "      <td>216.15</td>\n",
       "      <td>37967102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-10-11 00:00:00-04:00</th>\n",
       "      <td>111.360</td>\n",
       "      <td>111.54</td>\n",
       "      <td>111.350</td>\n",
       "      <td>111.49</td>\n",
       "      <td>2368028.0</td>\n",
       "      <td>213.45</td>\n",
       "      <td>215.74</td>\n",
       "      <td>212.580</td>\n",
       "      <td>215.66</td>\n",
       "      <td>97351296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-10-12 00:00:00-04:00</th>\n",
       "      <td>111.420</td>\n",
       "      <td>111.43</td>\n",
       "      <td>111.260</td>\n",
       "      <td>111.39</td>\n",
       "      <td>1459683.0</td>\n",
       "      <td>213.72</td>\n",
       "      <td>214.32</td>\n",
       "      <td>213.010</td>\n",
       "      <td>213.59</td>\n",
       "      <td>59594936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-10-13 00:00:00-04:00</th>\n",
       "      <td>111.570</td>\n",
       "      <td>111.68</td>\n",
       "      <td>111.525</td>\n",
       "      <td>111.60</td>\n",
       "      <td>1651166.0</td>\n",
       "      <td>213.04</td>\n",
       "      <td>213.59</td>\n",
       "      <td>211.210</td>\n",
       "      <td>212.16</td>\n",
       "      <td>82701384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-10-14 00:00:00-04:00</th>\n",
       "      <td>111.335</td>\n",
       "      <td>111.61</td>\n",
       "      <td>111.330</td>\n",
       "      <td>111.47</td>\n",
       "      <td>2277119.0</td>\n",
       "      <td>213.09</td>\n",
       "      <td>214.69</td>\n",
       "      <td>213.030</td>\n",
       "      <td>214.16</td>\n",
       "      <td>71665455</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               AGG                                      \\\n",
       "                             close    high      low    open     volume   \n",
       "time                                                                     \n",
       "2016-10-10 00:00:00-04:00  111.530  111.54  111.390  111.47  1115398.0   \n",
       "2016-10-11 00:00:00-04:00  111.360  111.54  111.350  111.49  2368028.0   \n",
       "2016-10-12 00:00:00-04:00  111.420  111.43  111.260  111.39  1459683.0   \n",
       "2016-10-13 00:00:00-04:00  111.570  111.68  111.525  111.60  1651166.0   \n",
       "2016-10-14 00:00:00-04:00  111.335  111.61  111.330  111.47  2277119.0   \n",
       "\n",
       "                              SPY                                     \n",
       "                            close    high      low    open    volume  \n",
       "time                                                                  \n",
       "2016-10-10 00:00:00-04:00  216.11  216.70  215.985  216.15  37967102  \n",
       "2016-10-11 00:00:00-04:00  213.45  215.74  212.580  215.66  97351296  \n",
       "2016-10-12 00:00:00-04:00  213.72  214.32  213.010  213.59  59594936  \n",
       "2016-10-13 00:00:00-04:00  213.04  213.59  211.210  212.16  82701384  \n",
       "2016-10-14 00:00:00-04:00  213.09  214.69  213.030  214.16  71665455  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get 5 years' worth of historical data for SPY and AGG\n",
    "# (use a limit=1000 parameter to call the most recent 1000 days of data)\n",
    "\n",
    "#The 5 year time period is greater than 1000 days. I will use two dataframes to obtain the data from the Alpaca API and then concatenate them.\n",
    "\n",
    "df_portfolio_3_year = alpaca.get_barset(\n",
    "    tickers,\n",
    "    timeframe,\n",
    "    start = start_date1,\n",
    "    end = end_date1,\n",
    "    limit = 1000\n",
    ").df\n",
    "\n",
    "df_portfolio_2_year = alpaca.get_barset(\n",
    "    tickers,\n",
    "    timeframe,\n",
    "    start = start_date2,\n",
    "    end = end_date2,\n",
    "    limit = 1000\n",
    ").df\n",
    "\n",
    "\n",
    "# Concatenate dataframes\n",
    "df_portfolio_5_year = pd.concat((df_portfolio_3_year,df_portfolio_2_year),axis=\"rows\", join=\"inner\", sort=True).dropna()\n",
    "\n",
    "# Display sample data\n",
    "df_portfolio_5_year.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Configuring a Monte Carlo simulation to forecast 30 years cumulative returns\n",
    "\n",
    "# Set number of simulations\n",
    "num_sims = 500\n",
    "\n",
    "MC_portfolio = MCSimulation(\n",
    "    portfolio_data = df_portfolio_5_year,\n",
    "    weights = [0.6,0.4],\n",
    "    num_simulation = num_sims,\n",
    "    num_trading_days = 252*30\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running Monte Carlo simulation number 0.\n",
      "Running Monte Carlo simulation number 10.\n",
      "Running Monte Carlo simulation number 20.\n",
      "Running Monte Carlo simulation number 30.\n",
      "Running Monte Carlo simulation number 40.\n",
      "Running Monte Carlo simulation number 50.\n",
      "Running Monte Carlo simulation number 60.\n",
      "Running Monte Carlo simulation number 70.\n",
      "Running Monte Carlo simulation number 80.\n",
      "Running Monte Carlo simulation number 90.\n",
      "Running Monte Carlo simulation number 100.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Grep\\Documents\\2021\\Fintech\\homework\\Homework5\\MCForecastTools.py:117: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead.  To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  portfolio_cumulative_returns[n] = (1 + sim_df.fillna(0)).cumprod()\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running Monte Carlo simulation number 110.\n",
      "Running Monte Carlo simulation number 120.\n",
      "Running Monte Carlo simulation number 130.\n",
      "Running Monte Carlo simulation number 140.\n",
      "Running Monte Carlo simulation number 150.\n",
      "Running Monte Carlo simulation number 160.\n",
      "Running Monte Carlo simulation number 170.\n",
      "Running Monte Carlo simulation number 180.\n",
      "Running Monte Carlo simulation number 190.\n",
      "Running Monte Carlo simulation number 200.\n",
      "Running Monte Carlo simulation number 210.\n",
      "Running Monte Carlo simulation number 220.\n",
      "Running Monte Carlo simulation number 230.\n",
      "Running Monte Carlo simulation number 240.\n",
      "Running Monte Carlo simulation number 250.\n",
      "Running Monte Carlo simulation number 260.\n",
      "Running Monte Carlo simulation number 270.\n",
      "Running Monte Carlo simulation number 280.\n",
      "Running Monte Carlo simulation number 290.\n",
      "Running Monte Carlo simulation number 300.\n",
      "Running Monte Carlo simulation number 310.\n",
      "Running Monte Carlo simulation number 320.\n",
      "Running Monte Carlo simulation number 330.\n",
      "Running Monte Carlo simulation number 340.\n",
      "Running Monte Carlo simulation number 350.\n",
      "Running Monte Carlo simulation number 360.\n",
      "Running Monte Carlo simulation number 370.\n",
      "Running Monte Carlo simulation number 380.\n",
      "Running Monte Carlo simulation number 390.\n",
      "Running Monte Carlo simulation number 400.\n",
      "Running Monte Carlo simulation number 410.\n",
      "Running Monte Carlo simulation number 420.\n",
      "Running Monte Carlo simulation number 430.\n",
      "Running Monte Carlo simulation number 440.\n",
      "Running Monte Carlo simulation number 450.\n",
      "Running Monte Carlo simulation number 460.\n",
      "Running Monte Carlo simulation number 470.\n",
      "Running Monte Carlo simulation number 480.\n",
      "Running Monte Carlo simulation number 490.\n"
     ]
    },
    {
     "data": {
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       "      <td>0.999579</td>\n",
       "      <td>0.997323</td>\n",
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       "      <td>1.009525</td>\n",
       "      <td>0.992563</td>\n",
       "      <td>0.999032</td>\n",
       "      <td>0.998075</td>\n",
       "      <td>0.995086</td>\n",
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       "      <td>19.420892</td>\n",
       "      <td>5.317062</td>\n",
       "      <td>3.744227</td>\n",
       "      <td>4.111513</td>\n",
       "      <td>4.088634</td>\n",
       "      <td>4.842274</td>\n",
       "      <td>11.267573</td>\n",
       "      <td>4.096668</td>\n",
       "      <td>3.627352</td>\n",
       "      <td>6.810565</td>\n",
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       "      <th>7557</th>\n",
       "      <td>12.641078</td>\n",
       "      <td>5.431794</td>\n",
       "      <td>8.892383</td>\n",
       "      <td>6.134207</td>\n",
       "      <td>4.851815</td>\n",
       "      <td>8.728886</td>\n",
       "      <td>4.629578</td>\n",
       "      <td>16.102689</td>\n",
       "      <td>3.168878</td>\n",
       "      <td>4.806435</td>\n",
       "      <td>...</td>\n",
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       "      <td>5.337670</td>\n",
       "      <td>3.773031</td>\n",
       "      <td>4.119100</td>\n",
       "      <td>4.067532</td>\n",
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       "      <td>5.469074</td>\n",
       "      <td>8.864420</td>\n",
       "      <td>6.126806</td>\n",
       "      <td>4.842119</td>\n",
       "      <td>8.792502</td>\n",
       "      <td>4.658382</td>\n",
       "      <td>16.132912</td>\n",
       "      <td>3.154557</td>\n",
       "      <td>4.801384</td>\n",
       "      <td>...</td>\n",
       "      <td>19.473164</td>\n",
       "      <td>5.299703</td>\n",
       "      <td>3.778247</td>\n",
       "      <td>4.112186</td>\n",
       "      <td>4.047527</td>\n",
       "      <td>4.848093</td>\n",
       "      <td>11.326225</td>\n",
       "      <td>4.091778</td>\n",
       "      <td>3.615685</td>\n",
       "      <td>6.857336</td>\n",
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       "    <tr>\n",
       "      <th>7559</th>\n",
       "      <td>12.668364</td>\n",
       "      <td>5.476460</td>\n",
       "      <td>8.902394</td>\n",
       "      <td>6.132605</td>\n",
       "      <td>4.847225</td>\n",
       "      <td>8.861242</td>\n",
       "      <td>4.697292</td>\n",
       "      <td>16.097122</td>\n",
       "      <td>3.135159</td>\n",
       "      <td>4.779253</td>\n",
       "      <td>...</td>\n",
       "      <td>19.327441</td>\n",
       "      <td>5.284869</td>\n",
       "      <td>3.777680</td>\n",
       "      <td>4.096511</td>\n",
       "      <td>4.020615</td>\n",
       "      <td>4.852879</td>\n",
       "      <td>11.325230</td>\n",
       "      <td>4.115680</td>\n",
       "      <td>3.589971</td>\n",
       "      <td>6.867514</td>\n",
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       "    <tr>\n",
       "      <th>7560</th>\n",
       "      <td>12.722786</td>\n",
       "      <td>5.503462</td>\n",
       "      <td>8.880173</td>\n",
       "      <td>6.149659</td>\n",
       "      <td>4.900351</td>\n",
       "      <td>8.793864</td>\n",
       "      <td>4.701359</td>\n",
       "      <td>16.170411</td>\n",
       "      <td>3.142422</td>\n",
       "      <td>4.741988</td>\n",
       "      <td>...</td>\n",
       "      <td>19.459398</td>\n",
       "      <td>5.314758</td>\n",
       "      <td>3.784202</td>\n",
       "      <td>4.091843</td>\n",
       "      <td>4.029023</td>\n",
       "      <td>4.854433</td>\n",
       "      <td>11.358136</td>\n",
       "      <td>4.148681</td>\n",
       "      <td>3.584123</td>\n",
       "      <td>6.801073</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7561 rows × 500 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            0         1         2         3         4         5         6    \\\n",
       "0      1.000000  1.000000  1.000000  1.000000  1.000000  1.000000  1.000000   \n",
       "1      1.007940  0.998782  1.004893  1.000230  1.001115  1.013851  1.005226   \n",
       "2      1.012273  0.996916  1.001325  1.003967  0.994870  1.013670  1.003279   \n",
       "3      1.010121  1.001424  1.000151  1.008412  0.998222  1.010225  0.998690   \n",
       "4      1.006059  1.009734  0.996988  1.001909  0.990337  1.006927  1.001148   \n",
       "...         ...       ...       ...       ...       ...       ...       ...   \n",
       "7556  12.694141  5.415080  8.894717  6.093284  4.824368  8.719197  4.626735   \n",
       "7557  12.641078  5.431794  8.892383  6.134207  4.851815  8.728886  4.629578   \n",
       "7558  12.654187  5.469074  8.864420  6.126806  4.842119  8.792502  4.658382   \n",
       "7559  12.668364  5.476460  8.902394  6.132605  4.847225  8.861242  4.697292   \n",
       "7560  12.722786  5.503462  8.880173  6.149659  4.900351  8.793864  4.701359   \n",
       "\n",
       "            7         8         9    ...        490       491       492  \\\n",
       "0      1.000000  1.000000  1.000000  ...   1.000000  1.000000  1.000000   \n",
       "1      0.992016  1.003085  0.994229  ...   1.000870  1.001066  0.994299   \n",
       "2      0.998433  1.008327  1.007219  ...   1.011007  0.999579  0.997323   \n",
       "3      0.992268  1.013029  0.999495  ...   1.012569  1.006145  0.998897   \n",
       "4      0.993556  1.011100  0.993117  ...   1.013942  1.010539  1.001633   \n",
       "...         ...       ...       ...  ...        ...       ...       ...   \n",
       "7556  16.139144  3.177394  4.810103  ...  19.420892  5.317062  3.744227   \n",
       "7557  16.102689  3.168878  4.806435  ...  19.466416  5.337670  3.773031   \n",
       "7558  16.132912  3.154557  4.801384  ...  19.473164  5.299703  3.778247   \n",
       "7559  16.097122  3.135159  4.779253  ...  19.327441  5.284869  3.777680   \n",
       "7560  16.170411  3.142422  4.741988  ...  19.459398  5.314758  3.784202   \n",
       "\n",
       "           493       494       495        496       497       498       499  \n",
       "0     1.000000  1.000000  1.000000   1.000000  1.000000  1.000000  1.000000  \n",
       "1     0.990868  1.008983  1.002566   1.000934  0.996583  0.995531  1.003953  \n",
       "2     0.989376  1.009525  0.992563   0.999032  0.998075  0.995086  1.012363  \n",
       "3     0.993023  1.004487  0.994963   0.998022  0.998368  0.992634  1.004442  \n",
       "4     0.993392  0.995215  0.997612   0.997385  0.994073  0.996335  1.004480  \n",
       "...        ...       ...       ...        ...       ...       ...       ...  \n",
       "7556  4.111513  4.088634  4.842274  11.267573  4.096668  3.627352  6.810565  \n",
       "7557  4.119100  4.067532  4.842340  11.287189  4.105359  3.629010  6.825305  \n",
       "7558  4.112186  4.047527  4.848093  11.326225  4.091778  3.615685  6.857336  \n",
       "7559  4.096511  4.020615  4.852879  11.325230  4.115680  3.589971  6.867514  \n",
       "7560  4.091843  4.029023  4.854433  11.358136  4.148681  3.584123  6.801073  \n",
       "\n",
       "[7561 rows x 500 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Running a Monte Carlo simulation to forecast 30 years cumulative returns\n",
    "MC_portfolio.calc_cumulative_return()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot simulation outcomes\n",
    "line_plot = MC_portfolio.plot_simulation()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot probability distribution and confidence intervals\n",
    "dist_plot = MC_portfolio.plot_distribution()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Retirement Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "count           500.000000\n",
      "mean              7.693122\n",
      "std               3.717468\n",
      "min               1.425487\n",
      "25%               5.085643\n",
      "50%               7.055794\n",
      "75%               9.109512\n",
      "max              25.762717\n",
      "95% CI Lower      2.887331\n",
      "95% CI Upper     16.848914\n",
      "Name: 7560, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "# Fetch summary statistics from the Monte Carlo simulation results\n",
    "summary_tbl = MC_portfolio.summarize_cumulative_return()\n",
    "\n",
    "# Print summary statistics\n",
    "print(summary_tbl)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculate the expected portfolio return at the `95%` lower and upper confidence intervals based on a `$20,000` initial investment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There is a 95% chance that an initial investment of $20000 in the portfolio over the next 30 years will end within in the range of $57746.61 and $336978.28\n"
     ]
    }
   ],
   "source": [
    "# Set initial investment\n",
    "initial_investment = 20000\n",
    "\n",
    "# Use the lower and upper `95%` confidence intervals to calculate the range of the possible outcomes of our $20,000\n",
    "ci_lower = round(summary_tbl[8]*initial_investment,2)\n",
    "ci_upper = round(summary_tbl[9]*initial_investment,2)\n",
    "\n",
    "# Print results\n",
    "print(f\"There is a 95% chance that an initial investment of ${initial_investment} in the portfolio\"\n",
    "      f\" over the next 30 years will end within in the range of\"\n",
    "      f\" ${ci_lower} and ${ci_upper}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculate the expected portfolio return at the `95%` lower and upper confidence intervals based on a `50%` increase in the initial investment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There is a 95% chance that an initial investment of $30000.0 in the portfolio over the next 30 years will end within the range of $86619.92 and $505467.42\n"
     ]
    }
   ],
   "source": [
    "# Set initial investment\n",
    "initial_investment = 20000 * 1.5\n",
    "\n",
    "# Use the lower and upper `95%` confidence intervals to calculate the range of the possible outcomes of our $30,000\n",
    "ci_lower = round(summary_tbl[8]*initial_investment,2)\n",
    "ci_upper = round(summary_tbl[9]*initial_investment,2)\n",
    "\n",
    "# Print results\n",
    "print(f\"There is a 95% chance that an initial investment of ${initial_investment} in the portfolio\"\n",
    "      f\" over the next 30 years will end within the range of\"\n",
    "      f\" ${ci_lower} and ${ci_upper}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Optional Challenge - Early Retirement\n",
    "\n",
    "\n",
    "### Five Years Retirement Option"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Configuring a Monte Carlo simulation to forecast 5 years cumulative returns\n",
    "\n",
    "#Set number of simulations\n",
    "num_sims = 500\n",
    "\n",
    "MC_portfolio_5y = MCSimulation(\n",
    "    portfolio_data = df_portfolio_5_year,\n",
    "    weights = [0.8,0.2],  #changed weights of stocks vs. bonds for a more aggressive/riskier portfolio\n",
    "    num_simulation = num_sims,\n",
    "    num_trading_days = 252*5\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running Monte Carlo simulation number 0.\n",
      "Running Monte Carlo simulation number 10.\n",
      "Running Monte Carlo simulation number 20.\n",
      "Running Monte Carlo simulation number 30.\n",
      "Running Monte Carlo simulation number 40.\n",
      "Running Monte Carlo simulation number 50.\n",
      "Running Monte Carlo simulation number 60.\n",
      "Running Monte Carlo simulation number 70.\n",
      "Running Monte Carlo simulation number 80.\n",
      "Running Monte Carlo simulation number 90.\n",
      "Running Monte Carlo simulation number 100.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Grep\\Documents\\2021\\Fintech\\homework\\Homework5\\MCForecastTools.py:117: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead.  To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  portfolio_cumulative_returns[n] = (1 + sim_df.fillna(0)).cumprod()\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running Monte Carlo simulation number 110.\n",
      "Running Monte Carlo simulation number 120.\n",
      "Running Monte Carlo simulation number 130.\n",
      "Running Monte Carlo simulation number 140.\n",
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      "Running Monte Carlo simulation number 480.\n",
      "Running Monte Carlo simulation number 490.\n"
     ]
    },
    {
     "data": {
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       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.001667</td>\n",
       "      <td>1.006177</td>\n",
       "      <td>1.006150</td>\n",
       "      <td>0.999277</td>\n",
       "      <td>1.002416</td>\n",
       "      <td>1.006792</td>\n",
       "      <td>1.001143</td>\n",
       "      <td>0.995911</td>\n",
       "      <td>1.003044</td>\n",
       "      <td>1.001841</td>\n",
       "      <td>...</td>\n",
       "      <td>1.002329</td>\n",
       "      <td>1.001955</td>\n",
       "      <td>0.998867</td>\n",
       "      <td>1.003248</td>\n",
       "      <td>0.996495</td>\n",
       "      <td>1.000407</td>\n",
       "      <td>1.002301</td>\n",
       "      <td>0.996756</td>\n",
       "      <td>1.004109</td>\n",
       "      <td>1.002038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.998684</td>\n",
       "      <td>1.003673</td>\n",
       "      <td>1.002347</td>\n",
       "      <td>0.998496</td>\n",
       "      <td>1.003703</td>\n",
       "      <td>1.012742</td>\n",
       "      <td>1.004694</td>\n",
       "      <td>0.995853</td>\n",
       "      <td>1.002003</td>\n",
       "      <td>1.000971</td>\n",
       "      <td>...</td>\n",
       "      <td>1.002896</td>\n",
       "      <td>0.999098</td>\n",
       "      <td>0.999452</td>\n",
       "      <td>1.004147</td>\n",
       "      <td>0.999180</td>\n",
       "      <td>1.002446</td>\n",
       "      <td>1.002227</td>\n",
       "      <td>1.003751</td>\n",
       "      <td>1.000593</td>\n",
       "      <td>1.003362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.998897</td>\n",
       "      <td>1.008155</td>\n",
       "      <td>1.001912</td>\n",
       "      <td>0.992205</td>\n",
       "      <td>1.005511</td>\n",
       "      <td>1.018308</td>\n",
       "      <td>1.005514</td>\n",
       "      <td>0.994956</td>\n",
       "      <td>0.999669</td>\n",
       "      <td>1.002486</td>\n",
       "      <td>...</td>\n",
       "      <td>1.006919</td>\n",
       "      <td>1.003877</td>\n",
       "      <td>0.996627</td>\n",
       "      <td>1.004598</td>\n",
       "      <td>1.000938</td>\n",
       "      <td>1.000616</td>\n",
       "      <td>0.994334</td>\n",
       "      <td>1.004822</td>\n",
       "      <td>1.001624</td>\n",
       "      <td>0.997552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.994421</td>\n",
       "      <td>1.005860</td>\n",
       "      <td>1.003145</td>\n",
       "      <td>0.990780</td>\n",
       "      <td>1.002295</td>\n",
       "      <td>1.025012</td>\n",
       "      <td>1.003086</td>\n",
       "      <td>0.990428</td>\n",
       "      <td>0.999625</td>\n",
       "      <td>1.002258</td>\n",
       "      <td>...</td>\n",
       "      <td>1.009686</td>\n",
       "      <td>1.004520</td>\n",
       "      <td>0.995344</td>\n",
       "      <td>1.010996</td>\n",
       "      <td>1.000326</td>\n",
       "      <td>0.999344</td>\n",
       "      <td>1.001638</td>\n",
       "      <td>1.003164</td>\n",
       "      <td>1.003141</td>\n",
       "      <td>0.999637</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>1256</th>\n",
       "      <td>1.573598</td>\n",
       "      <td>1.345357</td>\n",
       "      <td>1.148109</td>\n",
       "      <td>1.111691</td>\n",
       "      <td>0.925540</td>\n",
       "      <td>1.174247</td>\n",
       "      <td>1.139864</td>\n",
       "      <td>1.185556</td>\n",
       "      <td>1.281141</td>\n",
       "      <td>1.090682</td>\n",
       "      <td>...</td>\n",
       "      <td>1.329917</td>\n",
       "      <td>1.090312</td>\n",
       "      <td>1.291922</td>\n",
       "      <td>1.205796</td>\n",
       "      <td>1.275957</td>\n",
       "      <td>1.080432</td>\n",
       "      <td>1.201275</td>\n",
       "      <td>1.184818</td>\n",
       "      <td>0.930954</td>\n",
       "      <td>1.387723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1257</th>\n",
       "      <td>1.559844</td>\n",
       "      <td>1.341830</td>\n",
       "      <td>1.138088</td>\n",
       "      <td>1.107211</td>\n",
       "      <td>0.925446</td>\n",
       "      <td>1.178673</td>\n",
       "      <td>1.138442</td>\n",
       "      <td>1.183869</td>\n",
       "      <td>1.285031</td>\n",
       "      <td>1.094746</td>\n",
       "      <td>...</td>\n",
       "      <td>1.331028</td>\n",
       "      <td>1.096601</td>\n",
       "      <td>1.282460</td>\n",
       "      <td>1.205696</td>\n",
       "      <td>1.279373</td>\n",
       "      <td>1.076631</td>\n",
       "      <td>1.202029</td>\n",
       "      <td>1.182634</td>\n",
       "      <td>0.933376</td>\n",
       "      <td>1.379362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1258</th>\n",
       "      <td>1.562575</td>\n",
       "      <td>1.345019</td>\n",
       "      <td>1.136068</td>\n",
       "      <td>1.106222</td>\n",
       "      <td>0.919968</td>\n",
       "      <td>1.179761</td>\n",
       "      <td>1.131779</td>\n",
       "      <td>1.181822</td>\n",
       "      <td>1.297312</td>\n",
       "      <td>1.098722</td>\n",
       "      <td>...</td>\n",
       "      <td>1.330323</td>\n",
       "      <td>1.099321</td>\n",
       "      <td>1.280836</td>\n",
       "      <td>1.199717</td>\n",
       "      <td>1.281015</td>\n",
       "      <td>1.075831</td>\n",
       "      <td>1.203302</td>\n",
       "      <td>1.186784</td>\n",
       "      <td>0.935535</td>\n",
       "      <td>1.381157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1259</th>\n",
       "      <td>1.556492</td>\n",
       "      <td>1.350850</td>\n",
       "      <td>1.138178</td>\n",
       "      <td>1.109404</td>\n",
       "      <td>0.925707</td>\n",
       "      <td>1.177887</td>\n",
       "      <td>1.135818</td>\n",
       "      <td>1.183393</td>\n",
       "      <td>1.300102</td>\n",
       "      <td>1.096400</td>\n",
       "      <td>...</td>\n",
       "      <td>1.331602</td>\n",
       "      <td>1.097096</td>\n",
       "      <td>1.286198</td>\n",
       "      <td>1.197928</td>\n",
       "      <td>1.279101</td>\n",
       "      <td>1.079874</td>\n",
       "      <td>1.206118</td>\n",
       "      <td>1.187097</td>\n",
       "      <td>0.940647</td>\n",
       "      <td>1.379464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1260</th>\n",
       "      <td>1.550414</td>\n",
       "      <td>1.348603</td>\n",
       "      <td>1.130655</td>\n",
       "      <td>1.110755</td>\n",
       "      <td>0.921518</td>\n",
       "      <td>1.178479</td>\n",
       "      <td>1.137444</td>\n",
       "      <td>1.175555</td>\n",
       "      <td>1.301581</td>\n",
       "      <td>1.091553</td>\n",
       "      <td>...</td>\n",
       "      <td>1.333500</td>\n",
       "      <td>1.094209</td>\n",
       "      <td>1.286292</td>\n",
       "      <td>1.199673</td>\n",
       "      <td>1.265116</td>\n",
       "      <td>1.086420</td>\n",
       "      <td>1.210200</td>\n",
       "      <td>1.179610</td>\n",
       "      <td>0.941671</td>\n",
       "      <td>1.380221</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1261 rows × 500 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           0         1         2         3         4         5         6    \\\n",
       "0     1.000000  1.000000  1.000000  1.000000  1.000000  1.000000  1.000000   \n",
       "1     1.001667  1.006177  1.006150  0.999277  1.002416  1.006792  1.001143   \n",
       "2     0.998684  1.003673  1.002347  0.998496  1.003703  1.012742  1.004694   \n",
       "3     0.998897  1.008155  1.001912  0.992205  1.005511  1.018308  1.005514   \n",
       "4     0.994421  1.005860  1.003145  0.990780  1.002295  1.025012  1.003086   \n",
       "...        ...       ...       ...       ...       ...       ...       ...   \n",
       "1256  1.573598  1.345357  1.148109  1.111691  0.925540  1.174247  1.139864   \n",
       "1257  1.559844  1.341830  1.138088  1.107211  0.925446  1.178673  1.138442   \n",
       "1258  1.562575  1.345019  1.136068  1.106222  0.919968  1.179761  1.131779   \n",
       "1259  1.556492  1.350850  1.138178  1.109404  0.925707  1.177887  1.135818   \n",
       "1260  1.550414  1.348603  1.130655  1.110755  0.921518  1.178479  1.137444   \n",
       "\n",
       "           7         8         9    ...       490       491       492  \\\n",
       "0     1.000000  1.000000  1.000000  ...  1.000000  1.000000  1.000000   \n",
       "1     0.995911  1.003044  1.001841  ...  1.002329  1.001955  0.998867   \n",
       "2     0.995853  1.002003  1.000971  ...  1.002896  0.999098  0.999452   \n",
       "3     0.994956  0.999669  1.002486  ...  1.006919  1.003877  0.996627   \n",
       "4     0.990428  0.999625  1.002258  ...  1.009686  1.004520  0.995344   \n",
       "...        ...       ...       ...  ...       ...       ...       ...   \n",
       "1256  1.185556  1.281141  1.090682  ...  1.329917  1.090312  1.291922   \n",
       "1257  1.183869  1.285031  1.094746  ...  1.331028  1.096601  1.282460   \n",
       "1258  1.181822  1.297312  1.098722  ...  1.330323  1.099321  1.280836   \n",
       "1259  1.183393  1.300102  1.096400  ...  1.331602  1.097096  1.286198   \n",
       "1260  1.175555  1.301581  1.091553  ...  1.333500  1.094209  1.286292   \n",
       "\n",
       "           493       494       495       496       497       498       499  \n",
       "0     1.000000  1.000000  1.000000  1.000000  1.000000  1.000000  1.000000  \n",
       "1     1.003248  0.996495  1.000407  1.002301  0.996756  1.004109  1.002038  \n",
       "2     1.004147  0.999180  1.002446  1.002227  1.003751  1.000593  1.003362  \n",
       "3     1.004598  1.000938  1.000616  0.994334  1.004822  1.001624  0.997552  \n",
       "4     1.010996  1.000326  0.999344  1.001638  1.003164  1.003141  0.999637  \n",
       "...        ...       ...       ...       ...       ...       ...       ...  \n",
       "1256  1.205796  1.275957  1.080432  1.201275  1.184818  0.930954  1.387723  \n",
       "1257  1.205696  1.279373  1.076631  1.202029  1.182634  0.933376  1.379362  \n",
       "1258  1.199717  1.281015  1.075831  1.203302  1.186784  0.935535  1.381157  \n",
       "1259  1.197928  1.279101  1.079874  1.206118  1.187097  0.940647  1.379464  \n",
       "1260  1.199673  1.265116  1.086420  1.210200  1.179610  0.941671  1.380221  \n",
       "\n",
       "[1261 rows x 500 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Running a Monte Carlo simulation to forecast 5 years cumulative returns\n",
    "MC_portfolio_5y.calc_cumulative_return()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot simulation outcomes\n",
    "line_plot_5y = MC_portfolio_5y.plot_simulation()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot probability distribution and confidence intervals\n",
    "dist_plot_5y = MC_portfolio_5y.plot_distribution()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "count           500.000000\n",
      "mean              1.197366\n",
      "std               0.147146\n",
      "min               0.790186\n",
      "25%               1.102030\n",
      "50%               1.186900\n",
      "75%               1.282701\n",
      "max               1.648363\n",
      "95% CI Lower      0.925934\n",
      "95% CI Upper      1.529209\n",
      "Name: 1260, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "# Fetch summary statistics from the Monte Carlo simulation results\n",
    "summary_tbl_5y = MC_portfolio_5y.summarize_cumulative_return()\n",
    "\n",
    "# Print summary statistics\n",
    "print(summary_tbl_5y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There is a 95% chance that an initial investment of $20000 in the portfolio over the next 5 years will end within in the range of $18518.68 and $30584.17\n"
     ]
    }
   ],
   "source": [
    "# Set initial investment\n",
    "initial_investment = 20000  #same initial investment as the 30 year retirement plan\n",
    "\n",
    "# Use the lower and upper `95%` confidence intervals to calculate the range of the possible outcomes of our $30,000\n",
    "ci_lower_5y = round(summary_tbl_5y[8]*initial_investment,2)\n",
    "ci_upper_5y = round(summary_tbl_5y[9]*initial_investment,2)\n",
    "\n",
    "# Print results\n",
    "print(f\"There is a 95% chance that an initial investment of ${initial_investment} in the portfolio\"\n",
    "      f\" over the next 5 years will end within in the range of\"\n",
    "      f\" ${ci_lower_5y} and ${ci_upper_5y}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ten Years Retirement Option"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Configuring a Monte Carlo simulation to forecast 10 years cumulative returns\n",
    "#Set number of simulations\n",
    "num_sims = 500\n",
    "\n",
    "MC_portfolio_10y = MCSimulation(\n",
    "    portfolio_data = df_portfolio_5_year,\n",
    "    weights = [0.8,0.2],  #changed weights of stocks vs. bonds for a more aggressive/riskier portfolio\n",
    "    num_simulation = num_sims,\n",
    "    num_trading_days = 252*10\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running Monte Carlo simulation number 0.\n",
      "Running Monte Carlo simulation number 10.\n",
      "Running Monte Carlo simulation number 20.\n",
      "Running Monte Carlo simulation number 30.\n",
      "Running Monte Carlo simulation number 40.\n",
      "Running Monte Carlo simulation number 50.\n",
      "Running Monte Carlo simulation number 60.\n",
      "Running Monte Carlo simulation number 70.\n",
      "Running Monte Carlo simulation number 80.\n",
      "Running Monte Carlo simulation number 90.\n",
      "Running Monte Carlo simulation number 100.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Grep\\Documents\\2021\\Fintech\\homework\\Homework5\\MCForecastTools.py:117: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead.  To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  portfolio_cumulative_returns[n] = (1 + sim_df.fillna(0)).cumprod()\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running Monte Carlo simulation number 110.\n",
      "Running Monte Carlo simulation number 120.\n",
      "Running Monte Carlo simulation number 130.\n",
      "Running Monte Carlo simulation number 140.\n",
      "Running Monte Carlo simulation number 150.\n",
      "Running Monte Carlo simulation number 160.\n",
      "Running Monte Carlo simulation number 170.\n",
      "Running Monte Carlo simulation number 180.\n",
      "Running Monte Carlo simulation number 190.\n",
      "Running Monte Carlo simulation number 200.\n",
      "Running Monte Carlo simulation number 210.\n",
      "Running Monte Carlo simulation number 220.\n",
      "Running Monte Carlo simulation number 230.\n",
      "Running Monte Carlo simulation number 240.\n",
      "Running Monte Carlo simulation number 250.\n",
      "Running Monte Carlo simulation number 260.\n",
      "Running Monte Carlo simulation number 270.\n",
      "Running Monte Carlo simulation number 280.\n",
      "Running Monte Carlo simulation number 290.\n",
      "Running Monte Carlo simulation number 300.\n",
      "Running Monte Carlo simulation number 310.\n",
      "Running Monte Carlo simulation number 320.\n",
      "Running Monte Carlo simulation number 330.\n",
      "Running Monte Carlo simulation number 340.\n",
      "Running Monte Carlo simulation number 350.\n",
      "Running Monte Carlo simulation number 360.\n",
      "Running Monte Carlo simulation number 370.\n",
      "Running Monte Carlo simulation number 380.\n",
      "Running Monte Carlo simulation number 390.\n",
      "Running Monte Carlo simulation number 400.\n",
      "Running Monte Carlo simulation number 410.\n",
      "Running Monte Carlo simulation number 420.\n",
      "Running Monte Carlo simulation number 430.\n",
      "Running Monte Carlo simulation number 440.\n",
      "Running Monte Carlo simulation number 450.\n",
      "Running Monte Carlo simulation number 460.\n",
      "Running Monte Carlo simulation number 470.\n",
      "Running Monte Carlo simulation number 480.\n",
      "Running Monte Carlo simulation number 490.\n"
     ]
    },
    {
     "data": {
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       "2516  1.340081  1.355355  1.782453  1.129672  1.680813  1.247506  1.022510  \n",
       "2517  1.340844  1.351279  1.784793  1.131478  1.676098  1.253539  1.024256  \n",
       "2518  1.343345  1.349242  1.791610  1.130045  1.672567  1.257139  1.021584  \n",
       "2519  1.335105  1.346775  1.794486  1.131196  1.671367  1.255015  1.026989  \n",
       "2520  1.337995  1.346111  1.798691  1.130778  1.660420  1.247802  1.029067  \n",
       "\n",
       "[2521 rows x 500 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Running a Monte Carlo simulation to forecast 10 years cumulative returns\n",
    "MC_portfolio_10y.calc_cumulative_return()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot simulation outcomes\n",
    "line_plot_10y = MC_portfolio_10y.plot_simulation()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot probability distribution and confidence intervals\n",
    "dist_plot_10y = MC_portfolio_10y.plot_distribution()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "count           500.000000\n",
      "mean              1.425290\n",
      "std               0.249718\n",
      "min               0.778346\n",
      "25%               1.246738\n",
      "50%               1.403608\n",
      "75%               1.591450\n",
      "max               2.176336\n",
      "95% CI Lower      0.998869\n",
      "95% CI Upper      1.967998\n",
      "Name: 2520, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "# Fetch summary statistics from the Monte Carlo simulation results\n",
    "summary_tbl_10y = MC_portfolio_10y.summarize_cumulative_return()\n",
    "\n",
    "# Print summary statistics\n",
    "print(summary_tbl_10y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There is a 95% chance that an initial investment of $20000 in the portfolio over the next 10 years will end within in the range of $19977.37 and $39359.97\n"
     ]
    }
   ],
   "source": [
    "# Set initial investment\n",
    "initial_investment = 20000  #same initial investment as the 30 year retirement plan\n",
    "\n",
    "# Use the lower and upper `95%` confidence intervals to calculate the range of the possible outcomes of our $30,000\n",
    "ci_lower_10y = round(summary_tbl_10y[8]*initial_investment,2)\n",
    "ci_upper_10y = round(summary_tbl_10y[9]*initial_investment,2)\n",
    "\n",
    "# Print results\n",
    "print(f\"There is a 95% chance that an initial investment of ${initial_investment} in the portfolio\"\n",
    "      f\" over the next 10 years will end within in the range of\"\n",
    "      f\" ${ci_lower_10y} and ${ci_upper_10y}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "1b96bea370aa25765d77d0a7c5b93f2dc962ef269c95db79ebc3fe3f05623299"
  },
  "kernelspec": {
   "display_name": "Python 3.8.8 64-bit ('FinTech': conda)",
   "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": "3.8.8"
  },
  "nteract": {
   "version": "0.28.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}