diff --git a/backtesting /backtest.ipynb b/backtesting /backtest.ipynb
deleted file mode 100644
index c135849..0000000
--- a/backtesting /backtest.ipynb	
+++ /dev/null
@@ -1,373 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import backtrader as bt\n",
-    "import datetime\n",
-    "import yfinance as yf\n",
-    "import seaborn as sns\n",
-    "import matplotlib.pyplot as plt \n",
-    "import plotly.graph_objects as go"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "cerebro = bt.Cerebro() "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "[*********************100%%**********************]  1 of 1 completed\n"
-     ]
-    }
-   ],
-   "source": [
-    "df=yf.download('NVDA', start='2020-06-22')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "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>Open</th>\n",
-       "      <th>High</th>\n",
-       "      <th>Low</th>\n",
-       "      <th>Close</th>\n",
-       "      <th>Adj Close</th>\n",
-       "      <th>Volume</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",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>2020-06-22</th>\n",
-       "      <td>9.300000</td>\n",
-       "      <td>9.531250</td>\n",
-       "      <td>9.273250</td>\n",
-       "      <td>9.526750</td>\n",
-       "      <td>9.498451</td>\n",
-       "      <td>398468000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-06-23</th>\n",
-       "      <td>9.551000</td>\n",
-       "      <td>9.642500</td>\n",
-       "      <td>9.407500</td>\n",
-       "      <td>9.450000</td>\n",
-       "      <td>9.421928</td>\n",
-       "      <td>375108000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-06-24</th>\n",
-       "      <td>9.476250</td>\n",
-       "      <td>9.556500</td>\n",
-       "      <td>9.144500</td>\n",
-       "      <td>9.235500</td>\n",
-       "      <td>9.208068</td>\n",
-       "      <td>449372000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-06-25</th>\n",
-       "      <td>9.355750</td>\n",
-       "      <td>9.505000</td>\n",
-       "      <td>9.182250</td>\n",
-       "      <td>9.490000</td>\n",
-       "      <td>9.461808</td>\n",
-       "      <td>376072000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2020-06-26</th>\n",
-       "      <td>9.500000</td>\n",
-       "      <td>9.500000</td>\n",
-       "      <td>9.125000</td>\n",
-       "      <td>9.155000</td>\n",
-       "      <td>9.127806</td>\n",
-       "      <td>592084000</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",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2024-06-13</th>\n",
-       "      <td>129.389999</td>\n",
-       "      <td>129.800003</td>\n",
-       "      <td>127.160004</td>\n",
-       "      <td>129.610001</td>\n",
-       "      <td>129.610001</td>\n",
-       "      <td>260704500</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2024-06-14</th>\n",
-       "      <td>129.960007</td>\n",
-       "      <td>132.839996</td>\n",
-       "      <td>128.320007</td>\n",
-       "      <td>131.880005</td>\n",
-       "      <td>131.880005</td>\n",
-       "      <td>309320400</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2024-06-17</th>\n",
-       "      <td>132.990005</td>\n",
-       "      <td>133.729996</td>\n",
-       "      <td>129.580002</td>\n",
-       "      <td>130.979996</td>\n",
-       "      <td>130.979996</td>\n",
-       "      <td>288504400</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2024-06-18</th>\n",
-       "      <td>131.139999</td>\n",
-       "      <td>136.330002</td>\n",
-       "      <td>130.690002</td>\n",
-       "      <td>135.580002</td>\n",
-       "      <td>135.580002</td>\n",
-       "      <td>294335100</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2024-06-20</th>\n",
-       "      <td>139.850006</td>\n",
-       "      <td>140.759995</td>\n",
-       "      <td>129.529999</td>\n",
-       "      <td>130.779999</td>\n",
-       "      <td>130.779999</td>\n",
-       "      <td>504887012</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>1006 rows × 6 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                  Open        High         Low       Close   Adj Close  \\\n",
-       "Date                                                                     \n",
-       "2020-06-22    9.300000    9.531250    9.273250    9.526750    9.498451   \n",
-       "2020-06-23    9.551000    9.642500    9.407500    9.450000    9.421928   \n",
-       "2020-06-24    9.476250    9.556500    9.144500    9.235500    9.208068   \n",
-       "2020-06-25    9.355750    9.505000    9.182250    9.490000    9.461808   \n",
-       "2020-06-26    9.500000    9.500000    9.125000    9.155000    9.127806   \n",
-       "...                ...         ...         ...         ...         ...   \n",
-       "2024-06-13  129.389999  129.800003  127.160004  129.610001  129.610001   \n",
-       "2024-06-14  129.960007  132.839996  128.320007  131.880005  131.880005   \n",
-       "2024-06-17  132.990005  133.729996  129.580002  130.979996  130.979996   \n",
-       "2024-06-18  131.139999  136.330002  130.690002  135.580002  135.580002   \n",
-       "2024-06-20  139.850006  140.759995  129.529999  130.779999  130.779999   \n",
-       "\n",
-       "               Volume  \n",
-       "Date                   \n",
-       "2020-06-22  398468000  \n",
-       "2020-06-23  375108000  \n",
-       "2020-06-24  449372000  \n",
-       "2020-06-25  376072000  \n",
-       "2020-06-26  592084000  \n",
-       "...               ...  \n",
-       "2024-06-13  260704500  \n",
-       "2024-06-14  309320400  \n",
-       "2024-06-17  288504400  \n",
-       "2024-06-18  294335100  \n",
-       "2024-06-20  504887012  \n",
-       "\n",
-       "[1006 rows x 6 columns]"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "feed=bt.feeds.PandasData(dataname=df)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<backtrader.feeds.pandafeed.PandasData at 0x7f465466bfd0>"
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "cerebro.adddata(feed)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<bound method Cerebro.run of <backtrader.cerebro.Cerebro object at 0x7f4654ebcee0>>"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "cerebro.run"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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-      "text/plain": [
-       "<Figure size 1500x1200 with 4 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "[[<Figure size 1500x1200 with 4 Axes>]]"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "%matplotlib inline\n",
-    "cerebro = bt.Cerebro()\n",
-    "#cerebro.broker.setcash(10000.0)\n",
-    "\n",
-    "\n",
-    "cerebro.adddata(bt.feeds.PandasData(dataname = df))\n",
-    "cerebro.run()\n",
-    "\n",
-    "plt.rcParams['figure.figsize'] = [15, 12]\n",
-    "plt.rcParams.update({'font.size': 12}) \n",
-    "cerebro.plot(iplot = False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1500x1200 with 3 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "[[<Figure size 1500x1200 with 3 Axes>]]"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "cerebro.plot(iplot=False, volume=False, style='candlestick')"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": ".venv",
-   "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": "3.8.10"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}