Update

.ipynb_checkpoints/CapiPort-checkpoint.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "37b7d816",
+   "id": "5f6ccd5b",
    "metadata": {},
    "source": [
     "# CapiPort - PORTFOLIO OPTIMISATION"
@@ -10,7 +10,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b66aca9c",
+   "id": "b1962897",
    "metadata": {},
    "source": [
     "    Two things to consider for Portfolio Optimisation:\n",
@@ -21,7 +21,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d0c0e49d",
+   "id": "9d025126",
    "metadata": {},
    "source": [
     "    Basic process of Portfolio Optimisation:\n",
@@ -52,7 +52,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "dbfe76bf",
+   "id": "76496c3d",
    "metadata": {},
    "source": [
     "## Importing the Libraries"
@@ -61,7 +61,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "id": "20883492",
+   "id": "bdaab00e",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -79,7 +79,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a0a3c96e",
+   "id": "0d4befd2",
    "metadata": {},
    "source": [
     "## Get Stock Data"
@@ -88,7 +88,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "id": "f3937e5a",
+   "id": "33dc5711",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -129,7 +129,7 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "id": "0a9e0e4e",
+   "id": "3fec74c6",
    "metadata": {},
    "outputs": [
     {
@@ -154,8 +154,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "2ad5b748",
+   "execution_count": 28,
+   "id": "70190a08",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -202,23 +202,42 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "afa17f35",
+   "execution_count": 33,
+   "id": "ebf6b6bf",
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "TATAPOWER.NS  :  0.0\n",
+      "TATAMOTORS.NS  :  0.236548217499089\n",
+      "TATASTEEL.NS  :  0.17568900379556238\n",
+      "ZOMATO.NS  :  0.07826482194498546\n",
+      "NHPC.NS  :  0.21116461887342103\n",
+      "NCC.NS  :  0.0\n",
+      "IREDA.NS  :  0.0\n",
+      "IRCON.NS  :  0.2983333378869751\n"
+     ]
+    }
+   ],
+   "source": [
+    "optimal_weights = optimize_portfolio(equity_data, risk_free_rate)\n",
+    "for i,j in zip(equity_list, optimal_weights):\n",
+    "    print(i, \" : \", j)"
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "a17e46ca",
+   "id": "2a5e7bdf",
    "metadata": {},
    "outputs": [],
    "source": []
   },
   {
    "cell_type": "markdown",
-   "id": "38f5c7c7",
+   "id": "3a6c6060",
    "metadata": {},
    "source": [
     "## <u>STEPS FOR IMPLEMENTING<u>\n",
@@ -246,7 +265,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "df48c03f",
+   "id": "e4137507",
    "metadata": {},
    "outputs": [],
    "source": []

CapiPort.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "db58d421",
+   "id": "5f6ccd5b",
    "metadata": {},
    "source": [
     "# CapiPort - PORTFOLIO OPTIMISATION"
@@ -10,7 +10,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a9c51b1c",
+   "id": "b1962897",
    "metadata": {},
    "source": [
     "    Two things to consider for Portfolio Optimisation:\n",
@@ -21,7 +21,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "80e6fed1",
+   "id": "9d025126",
    "metadata": {},
    "source": [
     "    Basic process of Portfolio Optimisation:\n",
@@ -50,9 +50,359 @@
     "        6) Final Result"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "ab093e0e",
+   "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>SYMBOL</th>\n",
+       "      <th>NAME OF COMPANY</th>\n",
+       "      <th>SERIES</th>\n",
+       "      <th>DATE OF LISTING</th>\n",
+       "      <th>PAID UP VALUE</th>\n",
+       "      <th>MARKET LOT</th>\n",
+       "      <th>ISIN NUMBER</th>\n",
+       "      <th>FACE VALUE</th>\n",
+       "      <th>Unnamed: 8</th>\n",
+       "      <th>YahooEquiv</th>\n",
+       "      <th>Yahoo_Equivalent_Code</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>20MICRONS</td>\n",
+       "      <td>20 Microns Limited</td>\n",
+       "      <td>EQ</td>\n",
+       "      <td>06-Oct-08</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INE144J01027</td>\n",
+       "      <td>5</td>\n",
+       "      <td>.NS</td>\n",
+       "      <td>20MICRONS.NS</td>\n",
+       "      <td>'20MICRONS.NS',</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>21STCENMGM</td>\n",
+       "      <td>21st Century Management Services Limited</td>\n",
+       "      <td>EQ</td>\n",
+       "      <td>03-May-95</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INE253B01015</td>\n",
+       "      <td>10</td>\n",
+       "      <td>.NS</td>\n",
+       "      <td>21STCENMGM.NS</td>\n",
+       "      <td>'21STCENMGM.NS',</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3IINFOTECH</td>\n",
+       "      <td>3i Infotech Limited</td>\n",
+       "      <td>EQ</td>\n",
+       "      <td>22-Apr-05</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INE748C01020</td>\n",
+       "      <td>10</td>\n",
+       "      <td>.NS</td>\n",
+       "      <td>3IINFOTECH.NS</td>\n",
+       "      <td>'3IINFOTECH.NS',</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3MINDIA</td>\n",
+       "      <td>3M India Limited</td>\n",
+       "      <td>EQ</td>\n",
+       "      <td>13-Aug-04</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INE470A01017</td>\n",
+       "      <td>10</td>\n",
+       "      <td>.NS</td>\n",
+       "      <td>3MINDIA.NS</td>\n",
+       "      <td>'3MINDIA.NS',</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>3PLAND</td>\n",
+       "      <td>3P Land Holdings Limited</td>\n",
+       "      <td>EQ</td>\n",
+       "      <td>19-Jul-95</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INE105C01023</td>\n",
+       "      <td>2</td>\n",
+       "      <td>.NS</td>\n",
+       "      <td>3PLAND.NS</td>\n",
+       "      <td>'3PLAND.NS',</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1660</th>\n",
+       "      <td>ZODJRDMKJ</td>\n",
+       "      <td>Zodiac JRD- MKJ Limited</td>\n",
+       "      <td>EQ</td>\n",
+       "      <td>19-Jul-95</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INE077B01018</td>\n",
+       "      <td>10</td>\n",
+       "      <td>.NS</td>\n",
+       "      <td>ZODJRDMKJ.NS</td>\n",
+       "      <td>'ZODJRDMKJ.NS',</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1661</th>\n",
+       "      <td>ZOTA</td>\n",
+       "      <td>Zota Health Care LImited</td>\n",
+       "      <td>EQ</td>\n",
+       "      <td>19-Aug-19</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INE358U01012</td>\n",
+       "      <td>10</td>\n",
+       "      <td>.NS</td>\n",
+       "      <td>ZOTA.NS</td>\n",
+       "      <td>'ZOTA.NS',</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1662</th>\n",
+       "      <td>ZUARI</td>\n",
+       "      <td>Zuari Agro Chemicals Limited</td>\n",
+       "      <td>EQ</td>\n",
+       "      <td>27-Nov-12</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INE840M01016</td>\n",
+       "      <td>10</td>\n",
+       "      <td>.NS</td>\n",
+       "      <td>ZUARI.NS</td>\n",
+       "      <td>'ZUARI.NS',</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1663</th>\n",
+       "      <td>ZUARIGLOB</td>\n",
+       "      <td>Zuari Global Limited</td>\n",
+       "      <td>BE</td>\n",
+       "      <td>12-Apr-95</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INE217A01012</td>\n",
+       "      <td>10</td>\n",
+       "      <td>.NS</td>\n",
+       "      <td>ZUARIGLOB.NS</td>\n",
+       "      <td>'ZUARIGLOB.NS',</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1664</th>\n",
+       "      <td>ZYDUSWELL</td>\n",
+       "      <td>Zydus Wellness Limited</td>\n",
+       "      <td>EQ</td>\n",
+       "      <td>13-Nov-09</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1</td>\n",
+       "      <td>INE768C01010</td>\n",
+       "      <td>10</td>\n",
+       "      <td>.NS</td>\n",
+       "      <td>ZYDUSWELL.NS</td>\n",
+       "      <td>'ZYDUSWELL.NS'</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1665 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          SYMBOL                           NAME OF COMPANY  SERIES  \\\n",
+       "0      20MICRONS                        20 Microns Limited      EQ   \n",
+       "1     21STCENMGM  21st Century Management Services Limited      EQ   \n",
+       "2     3IINFOTECH                       3i Infotech Limited      EQ   \n",
+       "3        3MINDIA                          3M India Limited      EQ   \n",
+       "4         3PLAND                  3P Land Holdings Limited      EQ   \n",
+       "...          ...                                       ...     ...   \n",
+       "1660   ZODJRDMKJ                   Zodiac JRD- MKJ Limited      EQ   \n",
+       "1661        ZOTA                  Zota Health Care LImited      EQ   \n",
+       "1662       ZUARI              Zuari Agro Chemicals Limited      EQ   \n",
+       "1663   ZUARIGLOB                      Zuari Global Limited      BE   \n",
+       "1664   ZYDUSWELL                    Zydus Wellness Limited      EQ   \n",
+       "\n",
+       "      DATE OF LISTING   PAID UP VALUE   MARKET LOT   ISIN NUMBER   FACE VALUE  \\\n",
+       "0           06-Oct-08               5            1  INE144J01027            5   \n",
+       "1           03-May-95              10            1  INE253B01015           10   \n",
+       "2           22-Apr-05              10            1  INE748C01020           10   \n",
+       "3           13-Aug-04              10            1  INE470A01017           10   \n",
+       "4           19-Jul-95               2            1  INE105C01023            2   \n",
+       "...               ...             ...          ...           ...          ...   \n",
+       "1660        19-Jul-95              10            1  INE077B01018           10   \n",
+       "1661        19-Aug-19              10            1  INE358U01012           10   \n",
+       "1662        27-Nov-12              10            1  INE840M01016           10   \n",
+       "1663        12-Apr-95              10            1  INE217A01012           10   \n",
+       "1664        13-Nov-09              10            1  INE768C01010           10   \n",
+       "\n",
+       "     Unnamed: 8     YahooEquiv Yahoo_Equivalent_Code  \n",
+       "0           .NS   20MICRONS.NS       '20MICRONS.NS',  \n",
+       "1           .NS  21STCENMGM.NS      '21STCENMGM.NS',  \n",
+       "2           .NS  3IINFOTECH.NS      '3IINFOTECH.NS',  \n",
+       "3           .NS     3MINDIA.NS         '3MINDIA.NS',  \n",
+       "4           .NS      3PLAND.NS          '3PLAND.NS',  \n",
+       "...         ...            ...                   ...  \n",
+       "1660        .NS   ZODJRDMKJ.NS       'ZODJRDMKJ.NS',  \n",
+       "1661        .NS        ZOTA.NS            'ZOTA.NS',  \n",
+       "1662        .NS       ZUARI.NS           'ZUARI.NS',  \n",
+       "1663        .NS   ZUARIGLOB.NS       'ZUARIGLOB.NS',  \n",
+       "1664        .NS   ZYDUSWELL.NS        'ZYDUSWELL.NS'  \n",
+       "\n",
+       "[1665 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "df = pd.read_csv(\"EQUITY_L.csv\")\n",
+    "\n",
+    "df.head(1665)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "bd091648",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0        20MICRONS.NS\n",
+       "1       21STCENMGM.NS\n",
+       "2       3IINFOTECH.NS\n",
+       "3          3MINDIA.NS\n",
+       "4           3PLAND.NS\n",
+       "            ...      \n",
+       "1660     ZODJRDMKJ.NS\n",
+       "1661          ZOTA.NS\n",
+       "1662         ZUARI.NS\n",
+       "1663     ZUARIGLOB.NS\n",
+       "1664     ZYDUSWELL.NS\n",
+       "Name: SYMBOL, Length: 1665, dtype: object"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df['SYMBOL']+'.NS'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "13602af6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0                             20 Microns Limited\n",
+       "1       21st Century Management Services Limited\n",
+       "2                            3i Infotech Limited\n",
+       "3                               3M India Limited\n",
+       "4                       3P Land Holdings Limited\n",
+       "                          ...                   \n",
+       "1660                     Zodiac JRD- MKJ Limited\n",
+       "1661                    Zota Health Care LImited\n",
+       "1662                Zuari Agro Chemicals Limited\n",
+       "1663                        Zuari Global Limited\n",
+       "1664                      Zydus Wellness Limited\n",
+       "Name: NAME OF COMPANY, Length: 1665, dtype: object"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[\"NAME OF COMPANY\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "6ec4509a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0        20MICRONS.NS'\n",
+       "1       21STCENMGM.NS'\n",
+       "2       3IINFOTECH.NS'\n",
+       "3          3MINDIA.NS'\n",
+       "4           3PLAND.NS'\n",
+       "             ...      \n",
+       "1660     ZODJRDMKJ.NS'\n",
+       "1661          ZOTA.NS'\n",
+       "1662         ZUARI.NS'\n",
+       "1663     ZUARIGLOB.NS'\n",
+       "1664      ZYDUSWELL.NS\n",
+       "Name: Yahoo_Equivalent_Code, Length: 1665, dtype: object"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": []
+  },
   {
    "cell_type": "markdown",
-   "id": "e630d5b1",
+   "id": "76496c3d",
    "metadata": {},
    "source": [
     "## Importing the Libraries"
@@ -61,7 +411,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "id": "7de120f8",
+   "id": "bdaab00e",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -79,7 +429,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "91fcb51f",
+   "id": "0d4befd2",
    "metadata": {},
    "source": [
     "## Get Stock Data"
@@ -88,7 +438,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "id": "4f30295f",
+   "id": "33dc5711",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -129,7 +479,7 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "id": "c2f02cbe",
+   "id": "3fec74c6",
    "metadata": {},
    "outputs": [
     {
@@ -155,7 +505,7 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "id": "b9cb34f2",
+   "id": "70190a08",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -203,7 +553,7 @@
   {
    "cell_type": "code",
    "execution_count": 33,
-   "id": "6af1a0ad",
+   "id": "ebf6b6bf",
    "metadata": {},
    "outputs": [
     {
@@ -230,14 +580,14 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "39b7e975",
+   "id": "2a5e7bdf",
    "metadata": {},
    "outputs": [],
    "source": []
   },
   {
    "cell_type": "markdown",
-   "id": "a672bdae",
+   "id": "3a6c6060",
    "metadata": {},
    "source": [
     "## <u>STEPS FOR IMPLEMENTING<u>\n",
@@ -265,7 +615,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "00d89b09",
+   "id": "e4137507",
    "metadata": {},
    "outputs": [],
    "source": []

CapiPort.py

@@ -0,0 +1,80 @@
+import yfinance as yf
+
+from scipy.optimize import minimize
+
+import pandas as pd
+import numpy as np
+import matplotlib.pyplot as plt
+
+def get_historical_returns(tickers, start_date, end_date):
+    """
+    Fetch historical returns data for the given tickers.
+
+    Args:
+    - tickers: list of strings, tickers of assets
+    - start_date: string, start date in the format 'YYYY-MM-DD'
+    - end_date: string, end date in the format 'YYYY-MM-DD'
+
+    Returns:
+    - pandas DataFrame, historical returns data
+    """
+    data = yf.download(tickers, start=start_date, end=end_date)['Adj Close']
+    returns = data.pct_change().dropna()
+    return returns
+
+def get_risk_free_rate_india():
+    """
+    Get the risk-free rate for the Indian market using the yield of the 10-year Indian Government Bond.
+
+    Returns:
+    - float, risk-free rate
+    """
+    # Ticker symbol for the 10-year Indian Government Bond yield
+    bond_ticker = 'INR=X'  # You can replace this with the actual ticker symbol for the bond
+
+    # Fetch the bond data
+    bond_data = yf.Ticker(bond_ticker)
+
+    # Get the latest yield
+    risk_free_rate_india = bond_data.history(period='1d')['Close'][-1] / 100
+    return risk_free_rate_india
+
+def sharpe_ratio(weights, returns, risk_free_rate):
+    """
+    Calculate the Sharpe Ratio of a portfolio.
+
+    Args:
+    - weights: array-like, weights of assets in the portfolio
+    - returns: pandas DataFrame, historical returns of assets
+    - risk_free_rate: float, risk-free rate of return
+
+    Returns:
+    - float, Sharpe Ratio of the portfolio
+    """
+    portfolio_return = np.sum(weights * returns.mean() * 252)  # 252 trading days in a year
+    portfolio_std_dev = np.sqrt(np.dot(weights.T, np.dot(returns.cov() * 252, weights)))
+    sharpe_ratio = (portfolio_return - risk_free_rate) / portfolio_std_dev
+    return -sharpe_ratio  # Minimize negative Sharpe Ratio for maximization
+
+
+
+def optimize_portfolio(returns, risk_free_rate):
+    """
+    Optimize portfolio to maximize the Sharpe Ratio.
+
+    Args:
+    - returns: pandas DataFrame, historical returns of assets
+    - risk_free_rate: float, risk-free rate of return
+
+    Returns:
+    - array, optimal weights of assets in the portfolio
+    """
+    num_assets = len(returns.columns)
+    initial_weights = np.array([1 / num_assets] * num_assets)
+    bounds = [(0, 1)] * num_assets  # Bounds for asset weights (0 <= weight <= 1)
+    constraints = ({'type': 'eq', 'fun': lambda weights: np.sum(weights) - 1})  # Sum of weights equals 1 constraint
+
+    optimized_result = minimize(sharpe_ratio, initial_weights, args=(returns, risk_free_rate),
+                                method='SLSQP', bounds=bounds, constraints=constraints)
+
+    return optimized_result.x

main.py

@@ -0,0 +1,31 @@
+import CapiPort
+import streamlit as st
+import pandas as pd
+
+df = pd.read_csv("EQUITY_L.csv")
+
+CompanySymbol = (df["SYMBOL"] + '.NS').to_list()
+CompanyName = df["NAME OF COMPANY"].to_list()
+
+CompanyDict = dict()
+
+for CSymbol, CName in zip(CompanySymbol, CompanyName):
+    CompanyDict[CName] = CSymbol
+
+EquitiesInvested = st.multiselect('Select Multiple Companies', CompanyName, default = None)
+
+st.write("Need at Least two Companies to provide the Optimal Portfolio.")
+
+if len(EquitiesInvested) > 1:
+    EquitiesInvested = [CompanyDict[i] for i in EquitiesInvested]
+
+    st.write(EquitiesInvested)
+
+    equity_data = CapiPort.get_historical_returns(EquitiesInvested, "1900-01-01", "2024-03-04")
+
+    risk_free_rate = CapiPort.get_risk_free_rate_india()
+
+    optimal_weights = CapiPort.optimize_portfolio(equity_data, risk_free_rate)
+
+    for i,j in zip(EquitiesInvested, optimal_weights):
+        st.write(i, " : ", j)