RBAA.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import riskfolio as rp\n",
    "import numpy as np\n",
    "from tqdm import tqdm\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use(\"dark_background\")\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "from fredapi import Fred\n",
    "key=''\n",
    "\n",
    "fred = Fred(api_key=key)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Regime based asset allocation\n",
    "\n",
    "* Prediction with Random Forest and Genetic Algorithm (in the other notebooks)\n",
    "    * Inflation 12 months ahead YoY inflation and Recession nowcasting (for out-of sample regime classification)\n",
    "    * One-month ahead asset returns\n",
    "* Define the economics regimes\n",
    "* Bayesian inference to combine predictions and past returns\n",
    "* Mean-CDaR Portfolio Optimization\n",
    "* Backtest\n",
    "\n",
    "Data sources: Fred, Yahoo Finance\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Regimes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data={}\n",
    "codes={'Inflation': 'CPIAUCSL','Recession':'USRECD','Infl Expectations': 'EXPINF1YR'}\n",
    "\n",
    "for i in codes.values():\n",
    "    data[i]=fred.get_series(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.DataFrame.from_dict(data).resample('MS').ffill()\n",
    "df.columns=codes.keys()\n",
    "df['Inflation']=df['Inflation'].pct_change(12)*100\n",
    "df['Infl Expectations']=df['Infl Expectations'].shift(12)\n",
    "\n",
    "predicted=pd.read_csv('inflation.csv',parse_dates=True,index_col=0)\n",
    "predicted.columns=['Predicted']\n",
    "df=df.join(predicted)\n",
    "\n",
    "\n",
    "df=df.join(pd.read_csv('recession.csv',parse_dates=True,index_col=0))\n",
    "df.columns=list(df.columns)[:-1]+['Nowcasting']\n",
    "\n",
    "df['Nowcasting']=df['Nowcasting'].shift(2)\n",
    "df.ffill(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>Inflation</th>\n",
       "      <th>Recession</th>\n",
       "      <th>Infl Expectations</th>\n",
       "      <th>Predicted</th>\n",
       "      <th>Nowcasting</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1854-12-01</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1855-01-01</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1855-02-01</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1855-03-01</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1855-04-01</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-01</th>\n",
       "      <td>8.995221</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.055189</td>\n",
       "      <td>8.346106</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-01</th>\n",
       "      <td>8.482130</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.073116</td>\n",
       "      <td>8.214937</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-08-01</th>\n",
       "      <td>8.249235</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.462413</td>\n",
       "      <td>8.761452</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-01</th>\n",
       "      <td>8.222410</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.684137</td>\n",
       "      <td>8.482970</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-01</th>\n",
       "      <td>7.292744</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.854368</td>\n",
       "      <td>8.482970</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2015 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Inflation  Recession  Infl Expectations  Predicted  Nowcasting\n",
       "1854-12-01        NaN        1.0                NaN        NaN         NaN\n",
       "1855-01-01        NaN        0.0                NaN        NaN         NaN\n",
       "1855-02-01        NaN        0.0                NaN        NaN         NaN\n",
       "1855-03-01        NaN        0.0                NaN        NaN         NaN\n",
       "1855-04-01        NaN        0.0                NaN        NaN         NaN\n",
       "...               ...        ...                ...        ...         ...\n",
       "2022-06-01   8.995221        0.0           2.055189   8.346106         0.0\n",
       "2022-07-01   8.482130        0.0           2.073116   8.214937         0.0\n",
       "2022-08-01   8.249235        0.0           2.462413   8.761452         0.0\n",
       "2022-09-01   8.222410        0.0           2.684137   8.482970         0.0\n",
       "2022-10-01   7.292744        0.0           1.854368   8.482970         0.0\n",
       "\n",
       "[2015 rows x 5 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=df.resample('MS').ffill()\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "split='2007-05-01'\n",
    "df_test=df.loc[split:]\n",
    "df_train=df.loc[:split]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_train['Recession'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_train['Inflation Binary']=pd.get_dummies(df_train['Infl Expectations'].rolling(4).mean()<df_train['Inflation'].rolling(24).mean(),drop_first=True)\n",
    "df_train['Recession Binary']=df_train['Recession']\n",
    "\n",
    "df_test['Inflation Binary']=pd.get_dummies(df_test['Infl Expectations'].rolling(12).mean()+2<df_test['Predicted'].rolling(4).mean(),drop_first=True)\n",
    "df_test['Recession Binary']=pd.get_dummies(df_test['Nowcasting']>0.5,drop_first=True)\n",
    "\n",
    "\n",
    "df_train['1984':][['Inflation Binary','Recession Binary']].plot()\n",
    "df_test[['Inflation Binary','Recession Binary']].plot()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>Regimi</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Recessione</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Stagflazione</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Crescita</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Crescita inflazionistica</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Regimi\n",
       "0                Recessione\n",
       "1              Stagflazione\n",
       "2                  Crescita\n",
       "3  Crescita inflazionistica"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_=pd.concat([df_train[['Inflation Binary','Recession Binary']],df_test[['Inflation Binary','Recession Binary']].iloc[1:]])\n",
    "\n",
    "regimi=pd.DataFrame(['Recessione', 'Stagflazione', 'Crescita', 'Crescita inflazionistica'],columns=['Regimi'])\n",
    "regimi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "regimes=np.zeros(len(df_))\n",
    "regimes[np.logical_and(df_['Inflation Binary']==1,df_['Recession Binary']==1)]=1\n",
    "regimes[np.logical_and(df_['Inflation Binary']==0,df_['Recession Binary']==0)]=2\n",
    "regimes[np.logical_and(df_['Inflation Binary']==1,df_['Recession Binary']==0)]=3\n",
    "\n",
    "pd.DataFrame(regimes,index=df_.index).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bond TR index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  6 of 6 completed\n"
     ]
    }
   ],
   "source": [
    "import yfinance\n",
    "assets={'Gold': '^XAU','10 years':'^TNX','5 years': '^FVX','S&P500':'^GSPC','Commodities':'^SPGSCI','Cash':'^IRX'}\n",
    "assets=dict(sorted(assets.items(), key=lambda item: item[1]))\n",
    "data_=yfinance.download(list(assets.values()))['Adj Close'].dropna()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Following Swinkels (2019):\n",
    "\n",
    "Given the yield-to-maturity and remaining maturity, the interest rate sensitivity or modified duration of a risk-free bond at par value can be approximated by\n",
    "$$\n",
    "D_{\\mathfrak{t}}\\left(Y_t, M_t\\right)=1 / Y_t \\cdot\\left[1-1 /\\left(1+0.5 \\cdot Y_t\\right)^{2 \\cdot M}{ }_t\\right],\n",
    "$$\n",
    "with $Y_t$ the yield-to-maturity at time $t$ and $M_t$ the remaining maturity of the bond at time $t$. The convexity $C_t$ of a par bond, which measures the non-linear relationship between the price and yield of a bond can be approximated with\n",
    "$$\n",
    "\\left.C_t\\left(Y_t, M_t\\right)=2 /\\left(Y_{\\mathrm{t}}^2\\right) \\cdot\\left[1-1 /\\left(1+0.5 \\cdot Y_{\\mathrm{t}}\\right)^{2 \\cdot M t}\\right)\\right]-\\left(2 \\cdot M_t\\right) /\\left[Y_t \\cdot\\left(1+0.5 \\cdot Y_t\\right)\\right]^{2 \\cdot M_t+1} .\n",
    "$$\n",
    "For better approximations, the dispersion in maturity of the bond portfolio is needed as an input, which we do not have available. Now, we can calculate the investment return over period $t$ when we know the yield at the beginning and the end of the period, and the maturity of the bond\n",
    "$$\n",
    "R_t\\left(Y_{\\mathrm{t}-1}, Y_t, M_t\\right)=Y_{\\mathrm{t}-1}-D_t \\cdot\\left(Y_t-Y_{t-1}\\right)+\\frac{1}{2} \\cdot C_{\\mathrm{t}} \\cdot\\left(Y_{\\mathrm{t}}-Y_{t-1}\\right)^2\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def bond_tr(y,m,k=(1/252)):\n",
    "    z=1+y*0.5\n",
    "    duration=(1-1/(z**(2*m)))/y\n",
    "    convexity=(2/(y**2))*(1-1/(z**(2*m)))-(2*m)/(y*(z)**(2*m))\n",
    "    b_rets=(1+y)**(1/252)-1-duration*(y-y.shift(1))+0.5*convexity*((y-y.shift(1))**2)\n",
    "    return (1+b_rets).cumprod()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Date'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_['^TNX']=bond_tr(data_['^TNX']/100,10)\n",
    "data_['^FVX']=bond_tr(data_['^FVX']/100,5)\n",
    "data_['^IRX']=bond_tr(data_['^IRX']/100,1,k=(91/252))\n",
    "\n",
    "data_[['^TNX','^FVX','^IRX']].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Returns analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>5 years</th>\n",
       "      <th>S&amp;P500</th>\n",
       "      <th>Cash</th>\n",
       "      <th>Commodities</th>\n",
       "      <th>10 years</th>\n",
       "      <th>Gold</th>\n",
       "      <th>Regime</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1984-01-05</th>\n",
       "      <td>0.001550</td>\n",
       "      <td>0.012172</td>\n",
       "      <td>0.000808</td>\n",
       "      <td>0.003477</td>\n",
       "      <td>0.001021</td>\n",
       "      <td>0.004047</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984-01-06</th>\n",
       "      <td>0.001923</td>\n",
       "      <td>0.002784</td>\n",
       "      <td>0.000900</td>\n",
       "      <td>-0.006930</td>\n",
       "      <td>0.002763</td>\n",
       "      <td>-0.034399</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984-01-07</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984-01-08</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984-01-09</th>\n",
       "      <td>-0.001058</td>\n",
       "      <td>-0.002245</td>\n",
       "      <td>0.000057</td>\n",
       "      <td>-0.000802</td>\n",
       "      <td>-0.000717</td>\n",
       "      <td>-0.032563</td>\n",
       "      <td>2.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-27</th>\n",
       "      <td>-0.002112</td>\n",
       "      <td>-0.002120</td>\n",
       "      <td>-0.000703</td>\n",
       "      <td>0.011938</td>\n",
       "      <td>-0.006862</td>\n",
       "      <td>0.007221</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-28</th>\n",
       "      <td>0.013195</td>\n",
       "      <td>0.019672</td>\n",
       "      <td>0.000321</td>\n",
       "      <td>0.029317</td>\n",
       "      <td>0.021871</td>\n",
       "      <td>0.066370</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-29</th>\n",
       "      <td>-0.002403</td>\n",
       "      <td>-0.021126</td>\n",
       "      <td>0.000243</td>\n",
       "      <td>-0.004591</td>\n",
       "      <td>-0.003324</td>\n",
       "      <td>0.012020</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-30</th>\n",
       "      <td>-0.002621</td>\n",
       "      <td>-0.015067</td>\n",
       "      <td>0.000495</td>\n",
       "      <td>-0.013040</td>\n",
       "      <td>-0.004544</td>\n",
       "      <td>0.015702</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-01</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>14150 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             5 years    S&P500      Cash  Commodities  10 years      Gold  \\\n",
       "Date                                                                        \n",
       "1984-01-05  0.001550  0.012172  0.000808     0.003477  0.001021  0.004047   \n",
       "1984-01-06  0.001923  0.002784  0.000900    -0.006930  0.002763 -0.034399   \n",
       "1984-01-07  0.000000  0.000000  0.000000     0.000000  0.000000  0.000000   \n",
       "1984-01-08  0.000000  0.000000  0.000000     0.000000  0.000000  0.000000   \n",
       "1984-01-09 -0.001058 -0.002245  0.000057    -0.000802 -0.000717 -0.032563   \n",
       "...              ...       ...       ...          ...       ...       ...   \n",
       "2022-09-27 -0.002112 -0.002120 -0.000703     0.011938 -0.006862  0.007221   \n",
       "2022-09-28  0.013195  0.019672  0.000321     0.029317  0.021871  0.066370   \n",
       "2022-09-29 -0.002403 -0.021126  0.000243    -0.004591 -0.003324  0.012020   \n",
       "2022-09-30 -0.002621 -0.015067  0.000495    -0.013040 -0.004544  0.015702   \n",
       "2022-10-01  0.000000  0.000000  0.000000     0.000000  0.000000  0.000000   \n",
       "\n",
       "            Regime  \n",
       "Date                \n",
       "1984-01-05     2.0  \n",
       "1984-01-06     2.0  \n",
       "1984-01-07     2.0  \n",
       "1984-01-08     2.0  \n",
       "1984-01-09     2.0  \n",
       "...            ...  \n",
       "2022-09-27     3.0  \n",
       "2022-09-28     3.0  \n",
       "2022-09-29     3.0  \n",
       "2022-09-30     3.0  \n",
       "2022-10-01     3.0  \n",
       "\n",
       "[14150 rows x 7 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "returns=data_.resample('D').ffill().join(pd.DataFrame(regimes,index=df_.index).resample('D').ffill())\n",
    "returns.iloc[:,:6]=returns.iloc[:,:6].pct_change()\n",
    "returns.columns=list(assets.keys())+['Regime']\n",
    "returns.dropna(inplace=True)\n",
    "returns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "returns_train=returns[returns.index < split]\n",
    "returns_test=returns[returns.index > split]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x720 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "fig = plt.figure(figsize=(10, 10))\n",
    "for i in range(0,4):\n",
    "    ax = fig.add_subplot(2,2,i+1)\n",
    "    sns.heatmap(returns_train[returns_train['Regime']==i].drop('Regime',axis=1).corr(),cmap='copper',ax=ax)\n",
    "    plt.title('Regime n. '+str(regimi.iloc[i].values[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x720 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "fig = plt.figure(figsize=(10, 10))\n",
    "for i in range(0,4):\n",
    "    ax = fig.add_subplot(2,2,i+1)\n",
    "    sns.heatmap(returns_test[returns_test['Regime']==i].drop('Regime',axis=1).corr(),cmap='copper',ax=ax)\n",
    "    plt.title('Regime n. '+str(regimi.iloc[i].values[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10, 10))\n",
    "for i in range(0,4):\n",
    "    ax = fig.add_subplot(2,2,i+1)\n",
    "    sns.histplot(returns_train[returns_train['Regime']==i].drop(['Regime'],axis=1),kde='True',ax=ax)\n",
    "    plt.title('Regime n. '+str(regimi.iloc[i].values[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bayesian inference (not considered in Portfolio Optimization for now)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's assume that the asset's returns follow a multivariate Gaussian distribution with an uncertain mean which every investor have to estimate. Therefore, we express our predictions based on Random Forest as:\n",
    "$$\n",
    "f_{p r}(\\mu) \\sim N\\left(\\mu_0, \\Psi_0\\right)\n",
    "$$\n",
    "where $\\mu_0$ e $\\Psi_0$ are the mean and variance of the prior distribution. The variance/covariance matrix $\\Psi_0$ rapresent the uncertainity about the mean $\\mu_0$ and is computed on residual errors of the regressor. \n",
    "Then the prior density can be expressed as:\n",
    "$$\n",
    "f_{p r}(\\mu) \\propto \\exp \\left\\{-\\frac{1}{2}\\left(\\mu-\\mu_0\\right)^{\\prime} \\Psi_0^{-1}\\left(\\mu-\\mu_0\\right)\\right\\}\n",
    "$$\n",
    "\n",
    "And the conditional likehood as:\n",
    "$$\n",
    "f(\\mathbf{Y} \\mid \\mu, \\Sigma) \\propto \\exp \\left\\{-\\frac{1}{2}(\\mu-\\widehat{\\mu})^{\\prime} T \\Sigma^{-1}(\\mu-\\widehat{\\mu})\\right\\}\n",
    "$$\n",
    "\n",
    " Applying Gauss theorem we obtain:\n",
    " $$\n",
    "f_{p o}\\left(\\mu_1 \\mid \\mathbf{Y}, \\Sigma_1\\right) \\propto \\exp \\left\\{-\\frac{1}{2}\\left(\\mu-\\mu_1\\right)^{\\prime} \\Sigma_1^{-1}\\left(\\mu-\\mu_1\\right)\\right\\}\n",
    "$$\n",
    "\n",
    "$$\n",
    "\\begin{aligned}\n",
    "\\mu_1 &=\\left[\\Psi_0^{-1}+T \\Sigma^{-1}\\right]^{-1}\\left(\\Psi_0^{-1} \\mu_0+T \\Sigma^{-1} \\widehat{\\mu}\\right) \\\\\n",
    "\\Sigma_1 &=\\left[\\Psi_0^{-1}+T \\Sigma^{-1}\\right]^{-1}\n",
    "\\end{aligned}\n",
    "$$\n",
    "\n",
    "Which implies:\n",
    "$$\n",
    "f\\left(R_{t+1} \\mid \\mu, \\Sigma\\right) \\sim N\\left(\\mu_1, \\Sigma+\\Sigma_1\\right)\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "xgb=(pd.read_csv('predictions.csv',index_col=0,parse_dates=True).resample('D').ffill()+1)**(1/(25))-1\n",
    "returns=returns.join(xgb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>5 years</th>\n",
       "      <th>S&amp;P500</th>\n",
       "      <th>Cash</th>\n",
       "      <th>Commodities</th>\n",
       "      <th>10 years</th>\n",
       "      <th>Gold</th>\n",
       "      <th>Regime</th>\n",
       "      <th>^FVX</th>\n",
       "      <th>^GSPC</th>\n",
       "      <th>^IRX</th>\n",
       "      <th>^SPGSCI</th>\n",
       "      <th>^TNX</th>\n",
       "      <th>^XAU</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",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1984-01-05</th>\n",
       "      <td>0.001550</td>\n",
       "      <td>0.012172</td>\n",
       "      <td>0.000808</td>\n",
       "      <td>0.003477</td>\n",
       "      <td>0.001021</td>\n",
       "      <td>0.004047</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984-01-06</th>\n",
       "      <td>0.001923</td>\n",
       "      <td>0.002784</td>\n",
       "      <td>0.000900</td>\n",
       "      <td>-0.006930</td>\n",
       "      <td>0.002763</td>\n",
       "      <td>-0.034399</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984-01-07</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984-01-08</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984-01-09</th>\n",
       "      <td>-0.001058</td>\n",
       "      <td>-0.002245</td>\n",
       "      <td>0.000057</td>\n",
       "      <td>-0.000802</td>\n",
       "      <td>-0.000717</td>\n",
       "      <td>-0.032563</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-27</th>\n",
       "      <td>-0.002112</td>\n",
       "      <td>-0.002120</td>\n",
       "      <td>-0.000703</td>\n",
       "      <td>0.011938</td>\n",
       "      <td>-0.006862</td>\n",
       "      <td>0.007221</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-0.000540</td>\n",
       "      <td>0.001454</td>\n",
       "      <td>-0.000482</td>\n",
       "      <td>-0.008011</td>\n",
       "      <td>-0.000905</td>\n",
       "      <td>-0.012524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-28</th>\n",
       "      <td>0.013195</td>\n",
       "      <td>0.019672</td>\n",
       "      <td>0.000321</td>\n",
       "      <td>0.029317</td>\n",
       "      <td>0.021871</td>\n",
       "      <td>0.066370</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-0.000540</td>\n",
       "      <td>0.001454</td>\n",
       "      <td>-0.000482</td>\n",
       "      <td>-0.008011</td>\n",
       "      <td>-0.000905</td>\n",
       "      <td>-0.012524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-29</th>\n",
       "      <td>-0.002403</td>\n",
       "      <td>-0.021126</td>\n",
       "      <td>0.000243</td>\n",
       "      <td>-0.004591</td>\n",
       "      <td>-0.003324</td>\n",
       "      <td>0.012020</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-0.000540</td>\n",
       "      <td>0.001454</td>\n",
       "      <td>-0.000482</td>\n",
       "      <td>-0.008011</td>\n",
       "      <td>-0.000905</td>\n",
       "      <td>-0.012524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-09-30</th>\n",
       "      <td>-0.002621</td>\n",
       "      <td>-0.015067</td>\n",
       "      <td>0.000495</td>\n",
       "      <td>-0.013040</td>\n",
       "      <td>-0.004544</td>\n",
       "      <td>0.015702</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-0.000540</td>\n",
       "      <td>0.001454</td>\n",
       "      <td>-0.000482</td>\n",
       "      <td>-0.008011</td>\n",
       "      <td>-0.000905</td>\n",
       "      <td>-0.012524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-10-01</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-0.001053</td>\n",
       "      <td>-0.003947</td>\n",
       "      <td>-0.000210</td>\n",
       "      <td>-0.005489</td>\n",
       "      <td>-0.001778</td>\n",
       "      <td>0.000222</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>14150 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             5 years    S&P500      Cash  Commodities  10 years      Gold  \\\n",
       "Date                                                                        \n",
       "1984-01-05  0.001550  0.012172  0.000808     0.003477  0.001021  0.004047   \n",
       "1984-01-06  0.001923  0.002784  0.000900    -0.006930  0.002763 -0.034399   \n",
       "1984-01-07  0.000000  0.000000  0.000000     0.000000  0.000000  0.000000   \n",
       "1984-01-08  0.000000  0.000000  0.000000     0.000000  0.000000  0.000000   \n",
       "1984-01-09 -0.001058 -0.002245  0.000057    -0.000802 -0.000717 -0.032563   \n",
       "...              ...       ...       ...          ...       ...       ...   \n",
       "2022-09-27 -0.002112 -0.002120 -0.000703     0.011938 -0.006862  0.007221   \n",
       "2022-09-28  0.013195  0.019672  0.000321     0.029317  0.021871  0.066370   \n",
       "2022-09-29 -0.002403 -0.021126  0.000243    -0.004591 -0.003324  0.012020   \n",
       "2022-09-30 -0.002621 -0.015067  0.000495    -0.013040 -0.004544  0.015702   \n",
       "2022-10-01  0.000000  0.000000  0.000000     0.000000  0.000000  0.000000   \n",
       "\n",
       "            Regime      ^FVX     ^GSPC      ^IRX   ^SPGSCI      ^TNX      ^XAU  \n",
       "Date                                                                            \n",
       "1984-01-05     2.0       NaN       NaN       NaN       NaN       NaN       NaN  \n",
       "1984-01-06     2.0       NaN       NaN       NaN       NaN       NaN       NaN  \n",
       "1984-01-07     2.0       NaN       NaN       NaN       NaN       NaN       NaN  \n",
       "1984-01-08     2.0       NaN       NaN       NaN       NaN       NaN       NaN  \n",
       "1984-01-09     2.0       NaN       NaN       NaN       NaN       NaN       NaN  \n",
       "...            ...       ...       ...       ...       ...       ...       ...  \n",
       "2022-09-27     3.0 -0.000540  0.001454 -0.000482 -0.008011 -0.000905 -0.012524  \n",
       "2022-09-28     3.0 -0.000540  0.001454 -0.000482 -0.008011 -0.000905 -0.012524  \n",
       "2022-09-29     3.0 -0.000540  0.001454 -0.000482 -0.008011 -0.000905 -0.012524  \n",
       "2022-09-30     3.0 -0.000540  0.001454 -0.000482 -0.008011 -0.000905 -0.012524  \n",
       "2022-10-01     3.0 -0.001053 -0.003947 -0.000210 -0.005489 -0.001778  0.000222  \n",
       "\n",
       "[14150 rows x 13 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "returns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def posterior(returns,i):\n",
    "    from scipy.stats import gmean\n",
    "    rets=returns.loc[returns.index<=returns.iloc[i].name][returns['Regime']==returns['Regime'].iloc[i]].drop('Regime',axis=1)\n",
    "    likehood=np.array(rets.iloc[:,:6])\n",
    "    prior=np.array(rets.iloc[:,6:])\n",
    "    mu_0=(prior[-1])\n",
    "\n",
    "    cov_0=(np.array(returns.iloc[:,:6].shift(-1))-returns.iloc[:,7:]).cov()\n",
    "\n",
    "    mu_l=gmean(likehood+1)-1\n",
    "    sigma_l=pd.DataFrame(likehood).cov()\n",
    "    n=rets.shape[0]\n",
    "\n",
    "    mu1=np.linalg.inv(np.linalg.inv(cov_0)+n*np.linalg.inv(sigma_l))@(np.linalg.inv(cov_0)@mu_0+n*np.linalg.inv(sigma_l)@mu_l)\n",
    "    sigma1=np.linalg.inv(np.linalg.inv(cov_0)+n*np.linalg.inv(sigma_l))\n",
    "    sigma_pred=sigma1+sigma_l\n",
    "\n",
    "    return mu1, sigma_pred\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "postmu,postvar,dates=[],[],[]\n",
    "start=returns.reset_index()[returns.index>=returns_test.index[0]].index[0]\n",
    "for i in range(start,len(returns)):\n",
    "    mu,var=posterior(returns,i)\n",
    "    postmu.append(mu)\n",
    "    postvar.append(var)\n",
    "    dates.append(returns.iloc[i].name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Last predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x720 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(15, 10))\n",
    "a=-2\n",
    "for i in range(0,6):\n",
    "    ax = fig.add_subplot(2,3,i+1)\n",
    "    x = (np.random.normal(postmu[a][0],postvar[a][i][i],size=100))\n",
    "    y = (np.random.normal(np.array(returns.iloc[:,i].mean()),returns.iloc[:,i].var(),size=100))\n",
    "    z=(np.random.normal(np.array(returns.iloc[a,i+7]),(np.array(returns.iloc[:,:6].shift(-1))-returns.iloc[:,7:]).applymap(lambda x: x + np.random.normal(0,(0.001**2))).iloc[:a].var()[i],size=100))\n",
    "    sns.kdeplot(x*100,label='Posterior',ax=ax)\n",
    "    sns.kdeplot(y*100,label='Sample',ax=ax)\n",
    "    sns.kdeplot(z*100,label='Prior',ax=ax)\n",
    "    plt.title(list(assets.keys())[i])\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Portfolio Optimization\n",
    "\n",
    "$$\n",
    "\\max _w \\quad R(w)-\\lambda \\phi_k(w)\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 5632/5632 [00:03<00:00, 1713.67it/s]\n"
     ]
    }
   ],
   "source": [
    "import riskfolio as rp\n",
    "w,dates=[],[]\n",
    "c=0\n",
    "for i in tqdm(range(start, len(returns))):\n",
    "    if returns.iloc[i].name.month!=returns.iloc[i-1].name.month:\n",
    "        port=rp.Portfolio(returns[returns['Regime']==returns['Regime'].iloc[i]].iloc[:i,:6])\n",
    "        port.assets_stats('hist','hist')\n",
    "        ww=port.optimization(obj='Utility',l=5)\n",
    "        \n",
    "        if isinstance(port.optimal, pd.DataFrame):\n",
    "            w.append(ww)\n",
    "        else:\n",
    "            w.append(pd.DataFrame([0,0,1,0,0,0]))\n",
    "        dates.append(returns.iloc[i].name)\n",
    "        c+=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "weights=pd.DataFrame(np.concatenate(w,axis=1),index=returns.columns[:6],columns=dates).T\n",
    "import matplotlib.dates as mdates\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "\n",
    "\n",
    "ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))\n",
    "weights.plot.bar(stacked=True,figsize=(10,6),ax=ax)\n",
    "ax.xaxis.set_major_locator(mdates.DayLocator(interval=20))\n",
    "\n",
    "fig.autofmt_xdate()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Backtest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def drawdown(x):\n",
    "    return (x-x.expanding().max())/x\n",
    "\n",
    "def stats(hist,m=365):\n",
    "    so=sortino(hist)\n",
    "    std=hist.pct_change().std()[0]*(m**0.5)\n",
    "    cagr=(((hist.iloc[-1]/hist.iloc[0])**(m/len(hist))-1)).values[0]\n",
    "    sh=cagr/std\n",
    "    dd=((hist-hist.expanding().max())/hist.expanding().max()).min()[0]\n",
    "    return cagr,std,sh,dd,so\n",
    "    \n",
    "def sortino(df,m=252):\n",
    "    df=df.iloc[:,0]\n",
    "    expected_return = (df[-1]/df[0])**(m/len(df))-1\n",
    "    df=df.pct_change().dropna()\n",
    "    downside_returns = df.loc[df < 0]\n",
    "    down_stdev = downside_returns.std()*(m**0.5)\n",
    "    sortino_ratio = (expected_return)/down_stdev\n",
    "    return sortino_ratio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "ret=data_.resample('D').ffill().pct_change().dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    }
   ],
   "source": [
    "usd=yfinance.download('EURUSD=X')['Adj Close'].resample('D').ffill().pct_change().dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "weights_w=weights.resample('D').ffill()\n",
    "ptfr=((ret.loc[weights_w.index]*np.array(weights_w)).sum(axis=1))*(1+usd.loc[weights_w.index])\n",
    "static=(ret.loc[split:].multiply([0.3,0.4,0.1,0,0.3,0]).sum(axis=1)+1).cumprod()\n",
    "\n",
    "ptf=(ptfr+1).cumprod()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x29717c48610>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(8,6))\n",
    "\n",
    "ptf.plot(label='Regime Based Asset Allocation')\n",
    "static.plot(label='60/40 Portfolio')\n",
    "(ret['2007':]['^GSPC']+1).cumprod().plot(label='S&P 500')\n",
    "plt.title('Wealth index')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "portf=[pd.DataFrame(ptf).dropna(),(returns_test[['S&P500']]+1).cumprod()*100,pd.DataFrame(static),]\n",
    "st=[]\n",
    "for i in portf:\n",
    "    st.append(stats(i))\n",
    "res=pd.DataFrame(st,index=['RBAA','SP500','6040'],columns=['CAGR','STD','Sharpe','maxDD','Sortino' ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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>CAGR</th>\n",
       "      <th>STD</th>\n",
       "      <th>Sharpe</th>\n",
       "      <th>maxDD</th>\n",
       "      <th>Sortino</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RBAA</th>\n",
       "      <td>0.064605</td>\n",
       "      <td>0.056598</td>\n",
       "      <td>1.141477</td>\n",
       "      <td>-0.102668</td>\n",
       "      <td>1.043244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SP500</th>\n",
       "      <td>0.058290</td>\n",
       "      <td>0.206959</td>\n",
       "      <td>0.281651</td>\n",
       "      <td>-0.567754</td>\n",
       "      <td>0.231700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6040</th>\n",
       "      <td>0.045967</td>\n",
       "      <td>0.077894</td>\n",
       "      <td>0.590117</td>\n",
       "      <td>-0.191808</td>\n",
       "      <td>0.508911</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           CAGR       STD    Sharpe     maxDD   Sortino\n",
       "RBAA   0.064605  0.056598  1.141477 -0.102668  1.043244\n",
       "SP500  0.058290  0.206959  0.281651 -0.567754  0.231700\n",
       "6040   0.045967  0.077894  0.590117 -0.191808  0.508911"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7316764476028044"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1.04**(14)-1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.09629403128429027"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(ptf[-1]-ptf.max())/ptf.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2022-03-08    2.885836\n",
       "Freq: D, dtype: float64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ptf[ptf==ptf.max()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.17525773195876293"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(1/0.97)/(1/1.14)-1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 360x144 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "res[['Sharpe','Sortino']].plot.bar(figsize=(5,2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAUQAAAEOCAYAAADxKW7MAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/YYfK9AAAACXBIWXMAAAsTAAALEwEAmpwYAAAedUlEQVR4nO3deVAUZ/4G8Gc4grKcijBkRNEAxhtw0aQ8ieCFEVxXBbIREwNWXKMkXkTdxLgbRV1LKNd4oFHcuNHNCoGsGkEQo0Z0FERUEIhgYGVEhHhrEPr3h535hQBy9AwN4/OpequY7nfm/U5X8tjHdL8KAAKIiAhGchdARNRWMBCJiEQMRCIiEQORiEjEQCQiEjEQiYhEJnIX8CxlZWW4du2a3GUQkYHp3r077O3t6yxv04F47do1eHl5yV0GERkYtVpd73IeMhMRiRiIREQiBiIRkYiBSEQkYiASEYkYiEREIp0E4tixY5Gbm4v8/HwsWbKkzvrg4GBkZWUhKysLJ0+exIABA3QxLBGRzglSmpGRkVBQUCD06NFDMDU1Fc6fPy/07t27Vp9XX31VsLGxEQAI48aNE9LT05v02Wq1WlJtbGxsbPW1hrJF8g+zBw8ejIKCAhQWFgIA9u7dC39/f+Tk5Gj7nDp1Svt3eno6unbtKnVYes7UCN9Ier+R4nUdVUKGTPIhs0qlQnFxsfZ1SUkJVCpVg/1nzZqFQ4cOSR2WiEjnJO8hKhSKOssEQai376hRozBr1iwMGzaswc8LDQ1FWFgYAMDOzk5qeURETSZ5D7GkpAROTk7a1127dsX169fr9Ovfvz+2b98Of39/VFRUNPh5MTEx8PLygpeXF8rLy6WWR0TUZJIDUa1Ww9XVFc7OzjA1NUVgYCASExNr9XFyckJcXBzefPNN5OfnSx2SiEgvJB8yV1dXY+7cuTh8+DCMjY3x+eef4/Lly5g9ezYAYOvWrfjoo4/QuXNnfPbZZwCAJ0+e8Ck2RNTmKPD0cnObpFarGZwEgFeZSbcayhbeqUJEJGIgEhGJGIhERCIGIhGRiIFIRCRiIBIRiRiIREQiBiIRkYiBSEQkYiASEYkYiEREIgYiEZGIgUhEJGIgEhGJGIhERCIGIhGRqFUmqu/Vqxe+//57PHr0CAsWLNDFkEREOid5CgEjIyNs2rQJvr6+KCkpgVqtRmJiYq15mSsqKjBv3jwEBARIHY6ISG8k7yH+eqL6qqoq7UT1v3bz5k2cPXsWVVVVUocjItKbVp+onoiorWrVieqbghPVE5FcWm2i+qbiRPVEJJdWmaieiKg9aJWJ6h0cHHD27FlYWVmhpqYG4eHh6NOnD+7evSv5CxAR6Qonqqd2gRPVky5xonoiokZIPmQmIsP0PO6Vcw+RiEjEQCQiEj23h8zrs0+1+L0L+r+qw0qIqK3gHiIRkei53UOU4nk82awLUvbKAd61RPrHPUQiIhEDkYhIxENmIgPG0xTNwz1EIiIRA5GISMRAJCISMRCJiEQMRCIiEQORiEjEQCQiEukkEMeOHYvc3Fzk5+djyZIl9faJjo5Gfn4+srKy4OHhoYthiYh0SnIgGhkZYdOmTRg/fjz69OmDoKAg9O7du1af8ePHw9XVFa6urggLC8PmzZulDktEpHOSA3Hw4MEoKChAYWEhqqqqsHfvXvj7+9fq4+/vj927dwMATp8+DRsbGyiVSqlDExHplORAVKlUKC4u1r4uKSmBSqVqdh8iIrlJvpdZoVDUWSYIQrP7/CI0NBRhYWEAADs7O6nlNUjKQ14XSBz7aPKVFr/X27eXxNHlw23e+rjNm0fyHmJJSQmcnJy0r7t27Yrr1683u88vYmJi4OXlBS8vL5SXP383lxORfCQHolqthqurK5ydnWFqaorAwEAkJibW6pOYmIgZM2YAAIYMGYLbt29Do9FIHZqISKckHzJXV1dj7ty5OHz4MIyNjfH555/j8uXLmD17NgBg69atOHjwICZMmICCggI8ePAAb731luTCiYh0TSfPQzx06BAOHTpUa9nWrVtrvZ47d64uhiIi0hveqUJEJGIgEhGJGIhERCIGIhGRiIFIRCRiIBIRiRiIREQiBiIRkYiBSEQkYiASEYkYiEREIgYiEZGIgUhEJGIgEhGJGIhERCIGIhGRSFIg2traIikpCXl5eUhKSoKNjU29/Xbs2IEbN24gOztbynBERHolKRAjIiKQkpICNzc3pKSkICIiot5+u3btwrhx46QMRUSkd5IC0d/fH7GxsQCA2NhYBAQE1Nvv+PHjqKiokDIUEZHeSQpEBwcH7ex5Go0G9vb2OimKiEgOjU4ylZycDKVSWWf5smXL9FJQa01UT0T0W40Goq+vb4Prbty4AaVSCY1GA6VSibKyMskFxcTEICYmBsDTOZ8NkbdvL7lLIKJ6SDpkTkxMREhICAAgJCQECQkJOimKiEgOkgIxMjISvr6+yMvLg6+vLyIjIwEAjo6OOHDggLbfv/71L5w6dQq9evVCcXEx3n77bWlVExHpgaSJ6isqKuDj41NneWlpKfz8/LSvg4ODpQxDRNQqeKcKEZGIgUhEJGIgEhGJGIhERCIGIhGRiIFIRCRiIBIRiRiIREQiBiIRkYiBSEQkYiASEYkYiEREIgYiEZGIgUhEJGIgEhGJGIhERCIGIhGRSFIg2traIikpCXl5eUhKSoKNjU2dPl27dkVqaiouX76MixcvYt68eVKGJCLSG0mBGBERgZSUFLi5uSElJQURERF1+jx58gQLFixAnz598Morr+DPf/4zevfuLWVYIiK9kDSnir+/P0aNGgUAiI2NRVpaWp1Q1Gg02sns7927h5ycHKhUKuTk5EgZmojauPY43a6kPUQHBwdt2Gk0Gtjb2z+zf/fu3eHh4YHTp09LGZaISC8a3UNMTk6GUqmss3zZsmXNGuh3v/sd9u/fj/DwcNy9e7fBfqGhoQgLCwMA2NnZNWsMIiIpGg1EX1/fBtfduHEDSqUSGo0GSqUSZWVl9Q9iYoL9+/djz549iI+Pf+Z4MTExiImJAQCo1erGyiMi0hlJh8yJiYkICQkBAISEhCAhIaHefjt27EBOTg42bNggZTgiIr2SFIiRkZHw9fVFXl4efH19ERkZCQBwdHTEgQMHAABDhw7FjBkz8NprryEzMxOZmZkYP3689MqJiHRM0lXmiooK+Pj41FleWloKPz8/AMDJkyehUCikDENE1Cp4pwoRkYiBSEQkYiASEYkYiEREIgYiEZGIgUhEJGIgEhGJGIhERCIGIhGRiIFIRCRiIBIRiRiIREQiBiIRkYiBSEQkYiASEYkYiEREIr1PVG9mZobTp0/j/PnzuHjxIlasWCFlSCIivdH7RPWPHz/Ga6+9Bnd3d7i7u2PcuHEYMmSIlGGJiPRCUiD6+/sjNjYWwNOJ6gMCAurtd//+fQCAqakpTE1NIQiClGGJiPSiVSaqNzIyQmZmJsrKypCcnIwzZ85IGZaISC9aZaL6mpoaeHh4wNraGvHx8ejbty8uXbpUb19OVE9EcmmViep/cfv2baSlpWHcuHENBiInqiciueh9ono7OztYW1sDADp06AAfHx/k5uZKGZaISC/0PlG9o6Mjjh49iqysLKjVaiQnJ2vXERG1JXqfqD47Oxuenp5ShiEiahW8U4WISMRAJCISMRCJiEQMRCIiEQORiEjEQCQiEjEQiYhEDEQiIhEDkYhIxEAkIhIxEImIRAxEIiIRA5GISMRAJCISMRCJiEQMRCIiEQORiEgkKRBtbW2RlJSEvLw8JCUlwcbGpuGBjIyQkZGBb775RsqQRER6IykQIyIikJKSAjc3N6SkpCAiIqLBvvPnz0dOTo6U4YiI9EpSIPr7+yM2NhYAEBsbi4CAgHr7qVQq+Pn5Yfv27VKGIyLSK0mTTDk4OECj0QAANBoN7O3t6+0XFRWFxYsXw9LSUspwAJ4epoeHh8PZ2RkKhULy5xkSQRBQVFSEqKgoVFZWyl0OUbvTaCAmJydDqVTWWb5s2bImDeDn54eysjJkZGRg5MiRjfYPDQ1FWFgYgKdzOv9WeHg4zp49i5UrV6K6urpJNTwvjI2N4efnh/DwcHz88cdyl0PU7jQaiL6+vg2uu3HjBpRKJTQaDZRKJcrKyur0GTp0KCZNmoQJEyagQ4cOsLKywj//+U+8+eab9X5mTEwMYmJiAABqtbrOemdnZ4ZhA6qrq3HgwAFMmTJF7lKI2iVJ5xATExMREhICAAgJCUFCQkKdPkuXLoWTkxN69OiBwMBApKamNhiGTaFQKBiGz1BdXc1TCUQtJCkQIyMj4evri7y8PPj6+iIyMhIA4OjoiAMHDuikQCKi1iLpokpFRQV8fHzqLC8tLYWfn1+d5ceOHcOxY8ekDFnH+uxTOv28Bf1fbbSPg4MDoqKi4OXlhcePH6OoqAjh4eHIz89HeHg4Vq9eDQcHB9y5c0f7nrFjx2LlypWwsrLCo0ePcOXKFSxatAjFxcXYuXMnRo4cidu3b0OhUOCDDz5AamqqTr8XETWOd6q0QHx8PNLS0uDi4oK+ffti6dKlcHBwAAAEBQVBrVZj8uTJ2v59+/bFxo0bERISgt69e8PDwwN79uyBs7Ozts+iRYvg4eGB8PBwbNmypbW/EhGBgdhs3t7eqKqqwtatW7XLsrKycOLECfTs2RMWFhZYvnw5goKCtOuXLFmCVatWITc3V7vsm2++wfHjx+t8/qlTp6BSqfT7JYioXgzEZurXrx/OnTtX77qgoCB8+eWXOH78OHr16oUuXboAeLqHmJGR0aTPHzduHL7++mtdlUtEzcBA1KHAwEDs3bsXgiAgLi4OU6dOrdOnU6dOyMzMxJUrV7BgwQLt8nXr1uGHH37AF198gVWrVrVm2UQkYiA206VLlzBo0KA6y/v37w9XV1ckJyejsLAQgYGB2sPmS5cuwdPTE8DTC1EeHh7Ytm0bLCwstO9ftGgRXFxcsHz5cu3tkETUuhiIzZSamgozMzO888472mW///3vER0djRUrVqBHjx7o0aMHVCoVVCoVunXrhrVr12LZsmV4+eWXte8xNzev89mCICA6OhpGRkYYM2ZMq3wfIvp/kn520xY05WcyujZ58mRERUUhIiICjx49QlFREby9vfHuu+/W6hcfH4/AwECsXbsW8+fPx+7du2FpaYlbt27hxx9/bPD2ur/97W9YvHgxkpKSWuPrEJGo3QeiHEpLSzF9+vRG+/36HOHBgwdx8ODBevu99dZbtV7HxcUhLi5OWpFE1Gw8ZCYiEjEQiYhEDEQiIhEDkYhIxEAkIhIxEImIRO3+Zzc1gm6nNTVSvN5on6VLlyI4OBjV1dWoqalBZWUlbG1tYWFhgS5duqCwsBAAMGfOHKxatQqOjo54/PgxXnjhBRw5cgTLly/H7du3dVo3EUnX7gOxtb3yyiuYOHEiPD098fPPP6Nz58544YUXUFpaipEjR2LhwoV4/fXaofrGG2/g3LlzMDU1xerVq5GQkIBRo0bJ8wWIqEGtMlF9YWEhLly4gMzMzHrnSWlPHB0dUV5ejp9//hkAcOvWLZSWljbpvVVVVVi8eDG6deuGAQMG6LNMImqBVpuo3tvbGx4eHvDy8pIypOySkpLg5OSEK1euYNOmTRgxYkSz3l9TU4OsrKxa9zUTUdvQKhPVG5L79+9j0KBBCAsLw82bN7Fv3z7tRFtNxUmgiNomSYHY1InqBUFAUlISzp49i9DQUClDtgk1NTU4duwYVqxYgblz5zZr2k8jIyP0798fOTk5eqyQiFpC7xPVA0/nZi4tLUWXLl2QnJyM3Nzceh+fDzQ+Ub3c3NzcUFNTg4KCAgCAu7s7rl271qT3mpiY4NNPP0VxcTGys7P1WSYRtYDeJ6oHoL3ocPPmTcTHx2Pw4MENBmJjE9X/VlN+JqNLFhYW2LhxI2xsbPDkyRMUFBRoA7whe/bswePHj2FmZoYjR47A39+/laolouaQ9LObXyaqX7NmTYMT1Zubm8PIyAj37t2Dubk5xowZg5UrV0oZVlYZGRkYOnRovevqm2bV29u7NcoiIh3Q+0T1Dg4OOHHiBM6fP48zZ87gwIEDOHz4sPTKiYh0TO8T1RcWFsLd3V3KMERErYL3MhMRiRiIREQiBiIRkYiBSEQkavdPuzmafEWnn+ft20unn9cUISEhWLduHUpKSmBhYYGrV6/ik08+walTpwAAO3fuxMiRI3Hnzh107NgR6enp+PDDD3H9+vVWr5XIkHEPsY3Yt28fPD094ebmhsjISMTFxdV6AMSiRYvg7u6OXr16ITMzE0ePHoWpqamMFRMZHgZiM3Xv3h05OTmIiYlBdnY2vvjiC4wePRonTpxAXl4evLy84OXlhZMnTyIjIwMnT56Em5sbAOD999/Hjh07AAD9+vVDdnY2OnbsWGeMtLQ0bNu2rcE7YKKioqDRaDB+/Hj9fVGi5xADsQVcXFwQHR2NAQMG4OWXX0ZwcDCGDRuGhQsXYunSpcjNzcWIESPg6emJjz76CKtWrQLwNMhcXFwQEBCAnTt3Yvbs2Xj48GG9Y2RkZDzzEWGNrSei5mv35xDlUFhYiIsXLwIALl26hJSUFABAdnY2nJ2dYW1tjdjYWLi6ukIQBO2hrSAImDlzJi5cuICtW7fi+++/b3CMxh4RxkeIEeke9xBb4PHjx9q/a2pqtK9rampgYmKCv/71rzh69Cj69++P119/HR06dND2d3V1xb179/Diiy8+cwwPD49nPiKssfVE1HwMRD2wtrbG//73PwDAzJkztcutrKwQHR2NESNGoHPnzg0+R3HEiBEICwvTPvXnt9577z04Ojri22+/1XntRM+zdn/ILMfPZBqzdu1axMbG4oMPPkBqaqp2+YYNG/DZZ58hPz8fs2bNwtGjR/Hdd98BAKZPn45hw4bB3NwchYWFmDJlCnJzc7XvXbduHf7yl7/A3Nwc6enp8Pb2RlVVVat/NyJDpgAgyF1EQ9RqdZ05WHbv3o0ZM2bIVFH7wG1Ul5Tfq7bFf3RJmvqyBTCAPUSipmCoUVPwHCIRkajdBaIgCDA2Npa7jDbL2NgYgtBmz4IQtWntLhCLiorg5+fHUKyHsbEx/Pz8UFRUJHcpRO2SpHOItra22LdvH5ydnVFUVIRp06bhp59+qtPP2toa27dvR79+/SAIAt5++22kp6e3aMyoqCiEh4djypQp/HHybwiCgKKiIkRFRcldClG7JbS0rVmzRliyZIkAQFiyZIkQGRlZb79du3YJs2bNEgAIpqamgrW1dZM+X61Wt7g2NjY2tobaM7Kl5R+am5srKJVKAYCgVCqF3NzcOn0sLS2Fq1ev6rpoNjY2tha3hrJF0jlEBwcHaDQaAIBGo4G9vX2dPj179sTNmzexc+dOZGRkICYmBubm5lKGJSLSi0YDMTk5GdnZ2XXapEmTmjSAiYkJPD09sXnzZnh6euL+/fuIiIhosH9oaCjUajXUajXs7Oya/k2IiCSSdKdKbm4uRo0aBY1GA6VSibS0tDqPpHJwcEB6ejp69OgBABg2bBgiIiIwceLERj+/rKwM165da2l5srGzs0N5ebncZTxXuM1bX3ve5t27d6/3iFbSVebExESEhIRgzZo1CAkJQUJCQp0+N27cQHFxMdzc3JCXl4fRo0fj8uXLTfr8+gpuDxq6LYj0h9u89RnqNm/xiclOnToJR44cEfLy8oQjR44Itra2AgDB0dFROHDggLbfwIEDBbVaLWRlZQnx8fGCjY2N7CdV9dl4MYjb/HloBrrNZS/A4JqB/ofSphu3Obe5Llq7u1OlPdi2bZvcJTx3uM1bnyFu8zb9+C8iotbEPUQiIhEDkYhIxEAkIhIxEPWka9euWLhwodxlEFEzcAoBHercuTOmTp2KoKAgqFQqxMfHy12SwerVqxf8/f2hUqkgCAKuX7+OxMTEWhNzkW6NGTMGAQEBtbZ5QkICDh8+LHdpOsOrzBJZWFhg8uTJCA4OhpubG+Lj4zF9+nQ4OTnJXZrBWrx4MYKCgrB3716UlJQAeLpHHhgYiL1792LNmjUyV2h4NmzYADc3N+zevbvWNp8xYwby8/MRHh4ub4E6JPuPIdtze/DggZCWliYMGzZMu+yHH36QvS5DbleuXBFMTEzqLDc1NRXy8vJkr88Q25UrVxpcZ0jbnOcQJVq6dCk6dOiAzZs348MPP0TPnj3lLsng1dTU4MUXX6yz3NHRETU1NTJUZPgePXpU733LXl5eePTokQwV6QcPmXWkR48eCAoKQmBgIFxdXfHxxx8jPj4e+fn5cpdmcMaOHYt//OMfyM/PR3FxMQCgW7ducHFxwdy5cw3qnFZb4eHhgc2bN8PS0lJ7yOzk5IQ7d+5gzpw5yMjIkLlC3WAg6kG/fv0QHByMadOmwcXFRe5yDJJCocDgwYOhUqmgUChQUlICtVrNPUQ9c3BwqLXNb9y4IXdJOif7cbshNjMzM2Hq1Kmy12HIzd7eXvDw8BDc3d0Fe3t72et53tq7774rew26bvzZjQ4ZGRlhzJgxCAoKwpgxY3DixAl89dVXcpdlcAYOHIgtW7bA2toaJSUlUCgU6Nq1K3766SfMmTMHmZmZcpdocN5///06y345fw48vQptCBiIOjB8+HAEBwfDz88PZ86cwdChQ9GzZ088fPhQ7tIM0q5duzB79mycOXOm1vIhQ4Zg586dcHd3l6cwA/bJJ5/g4MGDuHTpknb6X2NjY1haWspcme7JvpvanltxcbFw8uRJ4U9/+pNgYWEhAGjxLINsTWvP+plHfn6+7PUZYnNychK++uorITIyUujYsaMAGObPy7iHKNH+/fsREBCA6dOno7q6GgkJCRAEQe6yDNqhQ4fw3//+F7t379ZeZXZycsKMGTPw7bffylydYSouLsbUqVMxadIkJCcnG8wh8m/xKrOOeHt7IygoCBMmTICVlRVmzZqFgwcP4v79+3KXZpDGjRunvXXvlyueiYmJOHTokNylGTxzc3OsWLECQ4YMwciRI+UuR6cYiDpmYmKC8ePHIzAwEGPGjEGXLl3kLomImkH243ZDbR06dJC9BkNs/fv31/5tYmIiLFu2TEhISBA+/fRT7fktNt02KysrYfXq1UJOTo5w69Ytoby8XLh8+bKwevVqwdraWvb6dNV4655ELi4u2LlzJ9avXw+VSoWDBw/i7t27OH/+PPr27St3eQZp165d2r8jIyPh4uKC9evXo2PHjtiyZYt8hRmwf//736isrMSoUaPQuXNn2NnZwdvbG5WVlQb30zLZU7k9t+PHjwuhoaHCggULhJKSEuGPf/yjYGZmJvj4+Ajp6emy12eILSMjQ/t3ZmZmrQc9ZGVlyV6fIbbc3NwWrWtvjXuIEllYWCAmJgbr16/Hw4cP8Z///AePHz/GkSNHYGZmJnd5Bsna2hoBAQH4wx/+ADMzMzx58kS7jlf49ePatWtYtGgR7O3ttcvs7e2xePFi7ZV+Q8BAlOjX987euXOnwXWkO8eOHcOkSZMwceJEpKena/8ndXBwQHl5uczVGabp06ejc+fOOHbsGCoqKnDr1i2kpaWhU6dOmDZtmtzl6QyvMkt0//59FBQUQKFQ4KWXXkJBQQGApw8f6NmzJywsLGSukEi6wYMHIzc3F3fu3EHHjh0REREBT09PXLp0CatWraqzM9BeMRAl6tat2zPX//jjj61UyfPDxcUF69atg4uLC7Kzs7Fw4UJcv35d7rIM2sWLFzFw4EBUV1dj69atuH//Pvbv34/Ro0dj4MCBmDJlitwl6ozsJzINsRkZGQnBwcGy12GI7bvvvhPeeecdwc3NTVi4cKGwf/9+2Wsy9Hb58mXt3+fOnau1LjMzU/b6dNV4DlEiS0tLREREYOPGjfD19QUAzJ07F1evXjWocyttiaWlJbZv3468vDz8/e9/h7Ozs9wlGbyLFy9i5syZAICsrCwMGjQIAODq6oqqqioZK9MtHjJL9PXXX6OyshKnTp3C6NGjYWtrixdeeAHz589HVlaW3OUZpJycHAQFBWmfurJnzx688cYb2vV8/JfuWVlZITo6GsOHD0d5eTk8PT1RXFyM4uJizJs3DxcuXJC7RJ1gIEp04cIFDBgwAMDT5yGWl5ejW7duuHfvnsyVGa7U1FQIgqANRAC1fm4zevRoOcp6LlhYWKBnz54wMTFBSUkJysrK5C5J52Q/bm/P7bfnU377mk33zcvLS1AqldrXM2bMEBISEoTo6GjB1tZW9vrY2m/jHqJET5480T7RRqFQoGPHjnjw4AEUCgUEQYC1tbXMFRqec+fOwcfHB5WVlRg+fDj27t2L9957D+7u7ujduzemTp0qd4nUTvF5iBKZmHATtjZjY2NUVlYCePqD4W3btiEuLg5xcXE8f0iS8CoztTvGxsYwNjYG8PR8YWpqqnYd/4EiKfhfD7U7X375JY4dO4by8nI8fPgQx48fBwC89NJLuH37tszVUXvGc4jULg0ZMgSOjo5ISkrCgwcPADz9TZyFhQUPm6nFGIhERCKeQyQiEjEQiYhEDEQiIhEDkYhIxEAkIhL9HwBQB7ZPj3epAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 360x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "res[['CAGR','STD','maxDD']].plot.bar(figsize=(5,4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.9.12 ('base')",
   "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": "3.9.12"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "4f7527b0034a603a2f6ced09004f8a888be406f0f25f6fb9b2bc8cc71cf9bc4b"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}