berry_cox_final_justin_defne.ipynb

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   "source": [
    "# Berry Cox's Price Momentum Final Project - Justin & Defne "
   ]
  },
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   "source": [
    "---\n",
    "## Primary Objective: Select Baskets of Assets for a long-short portfolio based on Berry Cox's Prcie Momentum Factors. Backtest for 5 years to check the performance of the algorithm.\n",
    "---"
   ]
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    "### Step 1: Choose an ETF with a minimum of 100 assets, identify those assets\n",
    "- We're using IVV ETF (IShares Core S&P 500 ETF)\n",
    "- We have a [CSV file](https://www.ishares.com/us/products/239726/ishares-core-sp-500-etf) with all their holdings to extract their assets\n",
    "- We'll download the asset information with Yahoo Finance\n",
    "\n",
    "### Step 2: Retrieve historical data for your chosen ETF\n",
    "- Using Adj Close for both, the IVV ETF and IVV Asset data"
   ]
  },
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   "source": [
    "# Importing our module \n",
    "import yfinance as yf \n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
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     "text": [
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
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   ],
   "source": [
    "# Retrieving Data for our chosen etf\n",
    "ivv_etf = yf.download('iVV', period='5y')['Adj Close']"
   ]
  },
  {
   "cell_type": "code",
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      "[*********************100%***********************]  502 of 502 completed\n"
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   "source": [
    "# Retrieving Data for our assets \n",
    "\n",
    "\"\"\"\n",
    "5 Failed downloads:\n",
    "- BRKB: No data found, symbol may be delisted\n",
    "- ESM3: No data found, symbol may be delisted\n",
    "- UBFUT: No data found, symbol may be delisted\n",
    "- XTSLA: No data found, symbol may be delisted\n",
    "- BFB: No data found, symbol may be delisted\n",
    "\n",
    "Since there's no data on these tickers we're just going to remove them from our dataframe\n",
    "\"\"\"\n",
    "ivv_assets_df = pd.read_csv('IVV_holdings.csv')[['Ticker', 'Name']].dropna()\n",
    "ivv_assets_df = ivv_assets_df.drop(index=ivv_assets_df.loc[ivv_assets_df['Ticker'].isin(['BRKB', 'ESM3', 'XTSLA', \"UBFUT\", \"XTSLA\", \"BFB\"])].index.tolist())\n",
    "ivv_asset_data = yf.download(tickers=ivv_assets_df['Ticker'].tolist(), period='5y')['Adj Close']  # accounting for the previous 5 years worth of data to help with the backtest "
   ]
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    "### Step 3: Calculate the price momentum factors for each asset in your ETF\n",
    "- Focusing on the 30 Day Price Momentum \n",
    "\n",
    "`Price Momentum = (CP - CPn) / CPn`\n",
    "\n",
    "Where: \n",
    "- CP = Closing price in the current period\n",
    "- CPn = Closing price N periods ago\n",
    "\n",
    "### Step 4: Using the price momentum factors, calculate the monthly z-factor score for each asset\n",
    "[Z-Factor Score Formula](https://www.khanacademy.org/math/statistics-probability/modeling-distributions-of-data/z-scores/a/z-scores-review)\n",
    "\n",
    "`Z-Factor Score = (Monthly Price Momentum Factor - Monthly Mean of Percent Change) / Monthly Standard Deviation`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "id": "faa2412a-e5c2-46b4-ba93-02c458659ac4",
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    "# Building a Python Class for our portfolio \n",
    "\n",
    "class Portfolio:\n",
    "    def __init__(self, etf_name, etf_data, etf_assets_df, etf_assets_data_df):\n",
    "            self.etf_name = etf_name\n",
    "            self.etf_data = etf_data # Current ETF Data (no assets information)\n",
    "            self.etf_assets_df = etf_assets_df # houses all the Tickers and Name for every asset in our ETF\n",
    "            self.etf_assets_data_df = etf_assets_data_df # getting the actually Adj Close Price of all our assets\n",
    "            self.etf_asset_info = pd.DataFrame(index=self.etf_assets_df['Ticker']) # Newly created DF to use Basket Information\n",
    "            \n",
    "            # monthly data\n",
    "            self.monthly_mean = self.etf_assets_data_df.groupby(pd.Grouper(freq='M')).mean()\n",
    "            self.monthly_std = self.etf_assets_data_df.pct_change().groupby(pd.Grouper(freq='M')).std()\n",
    "            \n",
    "    def get_baskets(self):\n",
    "        # Price Momentum Factor\n",
    "        self.etf_asset_info['Price Momentum Factor'] = (self.etf_assets_data_df.iloc[-1] - self.etf_assets_data_df.iloc[-31]) / self.etf_assets_data_df.iloc[-31]\n",
    "        \n",
    "        # Monthly Z-Factor Score  \n",
    "        monthly_pct_change_mean = self.etf_assets_data_df.pct_change().groupby(pd.Grouper(freq='M')).mean()\n",
    "        monthly_z_factor = (self.etf_asset_info['Price Momentum Factor'] - monthly_pct_change_mean.iloc[-1])/self.monthly_std.iloc[-1]\n",
    "        self.etf_asset_info['Monthly Z-Factor Score'] = abs(monthly_z_factor)\n",
    "        return self.etf_asset_info\n",
    "    \n",
    "    def get_smallest_basket(self):\n",
    "        # Getting 15 Smallest Z-factor Score for 15 Short Stocks \n",
    "        total_baskets = self.get_baskets()\n",
    "        smallest_basket = total_baskets.loc[total_baskets.index.isin(total_baskets['Monthly Z-Factor Score'].nsmallest(15).index.tolist())].sort_values('Monthly Z-Factor Score', )\n",
    "        return smallest_basket\n",
    "        \n",
    "    def get_largest_basket(self):\n",
    "        # Getting 15 Largest Z-factor Score for 15 Long Stocks \n",
    "        total_baskets = self.get_baskets()\n",
    "        largest_basket = total_baskets.loc[total_baskets.index.isin(total_baskets['Monthly Z-Factor Score'].nlargest(15).index.tolist())].sort_values('Monthly Z-Factor Score', )\n",
    "        return largest_basket\n",
    "    \n",
    "    def get_portfolio_basket(self):\n",
    "        # Returns the combination of 15 Long stocks and 15 Short Stocks\n",
    "        return pd.concat([self.get_smallest_basket(),self.get_largest_basket()]).sort_values('Monthly Z-Factor Score', ascending=False)\n",
    "    \n",
    "    def get_monthly_info(self,basket):\n",
    "        port_monthly_mean = self.monthly_mean[basket.index.tolist()].copy()\n",
    "        port_monthly_mean['Portfolio Monthly Return'] = port_monthly_mean[basket.index.tolist()].sum(axis=1)\n",
    "        port_monthly_mean['Portfolio Precent Change'] = port_monthly_mean[basket.index.tolist()].pct_change().sum(axis=1)\n",
    "        port_monthly_mean['Cumulative Monthly Return'] = port_monthly_mean['Portfolio Monthly Return'].cumsum()\n",
    "        port_monthly_mean['Cumulative Portfolio Percent Change'] = port_monthly_mean['Portfolio Precent Change'].cumsum()\n",
    "        \n",
    "        return port_monthly_mean\n",
    "    \n",
    "    def get_weighted_port_monthly_mean(self):\n",
    "        port_basket = self.get_portfolio_basket()\n",
    "        return self.get_monthly_info(port_basket)\n",
    "    \n",
    "    def get_etf_monthly_mean(self):\n",
    "        etf_df = self.etf_assets_data_df.groupby(pd.Grouper(freq='M')).mean() # 5-Year\n",
    "        etf_df['Portfolio Monthly Return'] = etf_df[self.etf_assets_data_df.columns.tolist()].sum(axis=1)\n",
    "        etf_df['Portfolio Precent Change'] = etf_df[self.etf_assets_data_df.columns.tolist()].pct_change().sum(axis=1)\n",
    "        etf_df['Cumulative Monthly Return'] = etf_df['Portfolio Monthly Return'].cumsum()\n",
    "        etf_df['Cumulative Portfolio Percent Change'] = etf_df['Portfolio Precent Change'].cumsum()\n",
    "        \n",
    "        return  etf_df\n",
    "    \n",
    "    def get_backtest_comparison(self):\n",
    "        final_comparison_df = pd.DataFrame(index=['BackTest Price Momentum Portfolio', 'BackTest IVV Portfolio'], columns=[\"Final Cumulative Value\", \"Final Cumulative Percent Change\"])\n",
    "        # Berry Cox\n",
    "        final_comparison_df.loc['BackTest Price Momentum Portfolio']['Final Cumulative Value'] = round(self.get_weighted_port_monthly_mean()[\"Cumulative Monthly Return\"].tail(1)[0],2)\n",
    "        final_comparison_df.loc['BackTest Price Momentum Portfolio']['Final Cumulative Percent Change'] = round(self.get_weighted_port_monthly_mean()[\"Cumulative Portfolio Percent Change\"].tail(1)[0],2)\n",
    "        \n",
    "        # ETF Port\n",
    "        final_comparison_df.loc[f'BackTest {self.etf_name} Portfolio']['Final Cumulative Value'] = round(self.get_etf_monthly_mean()[\"Cumulative Monthly Return\"].tail(1)[0],2)\n",
    "        final_comparison_df.loc[f'BackTest {self.etf_name} Portfolio']['Final Cumulative Percent Change'] = round(self.get_etf_monthly_mean()[\"Cumulative Portfolio Percent Change\"].tail(1)[0],2)\n",
    "        \n",
    "        return final_comparison_df\n",
    "    \n",
    "    def plot_information(self, plot_vars, ylabel=None, xlabel=None, title=None, figsize=(6,15), xlim=(0,100000)):\n",
    "        import matplotlib.pyplot as plt\n",
    "        f, ax = plt.subplots(figsize=figsize)\n",
    "        \n",
    "        \n",
    "        for plt in plot_vars:\n",
    "            sns.set_color_codes(plt['color_codes'])\n",
    "            sns.barplot(x=plt['x_values'], y=plt['y_values'], data=plt['data'], label=plt['label'], color=plt['color'])\n",
    "\n",
    "        # Add a legend and informative axis label\n",
    "        ax.legend(ncol=2, loc=\"upper right\", frameon=True)\n",
    "        ax.set(xlim=xlim, ylabel=ylabel, xlabel=xlabel, title=title)\n",
    "        sns.despine(left=True, bottom=True)\n",
    "\n",
    "    def __str__(self):\n",
    "        return self.etf_name"
   ]
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   "cell_type": "markdown",
   "id": "70feb15b-42e3-4b0a-b905-cfa906f3d378",
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   "source": [
    "### Step 5: Identify long and short baskets (10 to 15 assets in each) using calculated z-factors\n",
    "- Created a Function in the previous cell to get the total 30 Assets (15 Long and 15 Short)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "id": "8630a662-9a4e-45fd-9398-dff2b974a918",
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    {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Price Momentum Factor</th>\n",
       "      <th>Monthly Z-Factor Score</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ticker</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ISRG</th>\n",
       "      <td>0.215635</td>\n",
       "      <td>33.230911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CMG</th>\n",
       "      <td>0.197982</td>\n",
       "      <td>27.170161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MDLZ</th>\n",
       "      <td>0.109727</td>\n",
       "      <td>21.940489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EW</th>\n",
       "      <td>0.083729</td>\n",
       "      <td>20.168636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RSG</th>\n",
       "      <td>0.081576</td>\n",
       "      <td>20.007568</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Price Momentum Factor  Monthly Z-Factor Score\n",
       "Ticker                                               \n",
       "ISRG                 0.215635               33.230911\n",
       "CMG                  0.197982               27.170161\n",
       "MDLZ                 0.109727               21.940489\n",
       "EW                   0.083729               20.168636\n",
       "RSG                  0.081576               20.007568"
      ]
     },
     "execution_count": 214,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "ivv_port = Portfolio(etf_name=\"IVV\", etf_data=ivv_etf, etf_assets_df=ivv_assets_df, etf_assets_data_df=ivv_asset_data)\n",
    "ivv_port.get_portfolio_basket().head() # top 5 stocks in our portfolio "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57b65070-36b3-4049-97df-bfe94cb05199",
   "metadata": {},
   "source": [
    "### Step 6: Create a backtest to validate performance of your algorithm based on monthly restructuring over the previous 5 years.\n",
    "- Grouped Monthly over the past 5 years \n",
    "- Comparing the Cumulative Percent Change between our ETF (IVV) vs the Long-Short Basket"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "id": "09553af4-ddf2-4ed4-8749-9d8859daf615",
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   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Final Cumulative Value</th>\n",
       "      <th>Final Cumulative Percent Change</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>BackTest Price Momentum Portfolio</th>\n",
       "      <td>372612.8</td>\n",
       "      <td>20.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BackTest IVV Portfolio</th>\n",
       "      <td>4278293.89</td>\n",
       "      <td>304.27</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  Final Cumulative Value  \\\n",
       "BackTest Price Momentum Portfolio               372612.8   \n",
       "BackTest IVV Portfolio                        4278293.89   \n",
       "\n",
       "                                  Final Cumulative Percent Change  \n",
       "BackTest Price Momentum Portfolio                           20.42  \n",
       "BackTest IVV Portfolio                                     304.27  "
      ]
     },
     "execution_count": 210,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ivv_port.get_backtest_comparison()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6dd51739-c573-4b62-8ca7-daf03c013ff7",
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   "source": [
    "### Step 7: Chart\n",
    "1. Monthly portfolio return bar chart (pos/neg coloring) vs ETF\n",
    "1. Monthly return for long picks vs short picks vs ETF\n",
    "1. Cumulative portfolio return vs ETF"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa72e3b4-281c-48ec-91ab-65cae17949d9",
   "metadata": {},
   "source": [
    "## Monthly portfolio return bar chart (pos/neg coloring) vs ETF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "id": "d3dfd1fa-adf4-4733-81db-622bade3690a",
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   "outputs": [
    {
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\n",
      "text/plain": [
       "<Figure size 864x1080 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "monthly_port_return = [\n",
    "    # IVV Portfolio \n",
    "    {\n",
    "        'color_codes': 'pastel',\n",
    "        'x_values': ivv_port.get_etf_monthly_mean()[\"Portfolio Monthly Return\"] / 1000,\n",
    "        'y_values': [ts.strftime('%b %Y') for ts in ivv_port.get_etf_monthly_mean().index.tolist()],\n",
    "        'data': ivv_port.get_etf_monthly_mean(),\n",
    "        'label': \"IVV Portfolio\",\n",
    "        'color': \"b\"\n",
    "    },\n",
    "    #Our Portfolio\n",
    "    {\n",
    "        'color_codes': 'muted',\n",
    "        'x_values': ivv_port.get_weighted_port_monthly_mean()[\"Portfolio Monthly Return\"] / 1000,\n",
    "        'y_values': [ts.strftime('%b %Y') for ts in ivv_port.get_weighted_port_monthly_mean().index.tolist()],\n",
    "        'data': ivv_port.get_weighted_port_monthly_mean(),\n",
    "        'label': \"Our Portfolio in Thousands\",\n",
    "        'color': \"b\"\n",
    "    },\n",
    "]\n",
    "ivv_port.plot_information(plot_vars=monthly_port_return, ylabel=\"Date\", xlabel=\"Portfolio Return\",title='Monthly portfolio return bar chart (pos/neg coloring) vs ETF', figsize=(12,15), xlim=(0,100))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cdf47393-d834-4869-9a9f-8be885503112",
   "metadata": {},
   "source": [
    "## Monthly return for long picks vs short picks vs ETF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "id": "14d826c5-2d45-4bb0-9106-df408c2b167a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x1080 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "monthly_return_long_short_etf = [\n",
    "    # IVV Portfolio \n",
    "    {\n",
    "        'color_codes': 'pastel',\n",
    "        'x_values': ivv_port.get_etf_monthly_mean()[\"Portfolio Monthly Return\"] / 1000,\n",
    "        'y_values': [ts.strftime('%b %Y') for ts in ivv_port.get_etf_monthly_mean().index.tolist()],\n",
    "        'data': ivv_port.get_etf_monthly_mean(),\n",
    "        'label': \"IVV Portfolio\",\n",
    "        'color': \"b\"\n",
    "    },\n",
    "    # Short Portfolio\n",
    "    {\n",
    "        'color_codes': 'muted',\n",
    "        'x_values': ivv_port.get_monthly_info(ivv_port.get_smallest_basket())[\"Portfolio Monthly Return\"] / 1000,\n",
    "        'y_values': [ts.strftime('%b %Y') for ts in ivv_port.get_monthly_info(ivv_port.get_smallest_basket()).index.tolist()],\n",
    "        'data': ivv_port.get_monthly_info(ivv_port.get_smallest_basket()),\n",
    "        'label': \"Short Portfolio\",\n",
    "        'color': \"b\"\n",
    "    },\n",
    "    # Long Portfolio\n",
    "    {\n",
    "        'color_codes': 'dark',\n",
    "        'x_values': ivv_port.get_monthly_info(ivv_port.get_largest_basket())[\"Portfolio Monthly Return\"] / 1000,\n",
    "        'y_values': [ts.strftime('%b %Y') for ts in ivv_port.get_monthly_info(ivv_port.get_largest_basket()).index.tolist()],\n",
    "        'data': ivv_port.get_monthly_info(ivv_port.get_largest_basket()),\n",
    "        'label': \"Long Portfolio\",\n",
    "        'color': \"b\"\n",
    "    },\n",
    "]\n",
    "ivv_port.plot_information(plot_vars=monthly_return_long_short_etf, ylabel=\"Month\", xlabel=\"Portfolio Return in Thousands\",title='Monthly return for long picks vs short picks vs ETF', figsize=(12,15), xlim=(0,100))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36a5e75d-b576-4a9f-9cc3-94444cdc65f8",
   "metadata": {},
   "source": [
    "## Cumulative portfolio return vs ETF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "id": "dedede1b-2929-438c-ba9d-a9ea0d83dbf1",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cumulative_return_port_etf = [\n",
    "    # # IVV Portfolio \n",
    "    # {\n",
    "    #     'color_codes': 'pastel',\n",
    "    #     'x_values': \"Portfolio Monthly Return\",\n",
    "    #     'y_values': [ts.strftime('%b %Y') for ts in ivv_port.get_etf_monthly_mean().index.tolist()],\n",
    "    #     'data': ivv_port.get_backtest_comparison(),\n",
    "    #     'label': \"IVV Portfolio\",\n",
    "    #     'color': \"b\"\n",
    "    # },\n",
    "    # # Our Portfolio\n",
    "    {\n",
    "        'color_codes': 'muted',\n",
    "        'y_values': ivv_port.get_backtest_comparison()['Final Cumulative Value'] / 1000,\n",
    "        'x_values': ivv_port.get_backtest_comparison().index.tolist(),\n",
    "        'data': ivv_port.get_backtest_comparison(),\n",
    "        'label': None,\n",
    "        'color': None\n",
    "    },\n",
    "    \n",
    "]\n",
    "ivv_port.plot_information(plot_vars=cumulative_return_port_etf, xlabel=\"Portfolio\", ylabel=\"Cumulative Portfolio Return in Thousands\",title='Cumulative portfolio return vs ETF', figsize=(6,6), xlim=None)\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}