diff --git a/notebooks/backtesting_yfinance.ipynb b/notebooks/backtesting_yfinance.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Exploring data from Yahoo finance"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#import sys\n",
+    "#import os\n",
+    "#sys.path.append('../')\n",
+    "\n",
+    "#import yfinance as yf\n",
+    "#import backtrader as bt\n",
+    "#import pandas as pd\n",
+    "#from datetime import datetime"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from __future__ import (absolute_import, division, print_function,\n",
+    "                        unicode_literals)\n",
+    "\n",
+    "import datetime  \n",
+    "import os.path  \n",
+    "import sys  # To find out the script name (in argv[0])\n",
+    "import pandas as pd\n",
+    "\n",
+    "# Import the backtrader platform\n",
+    "import backtrader as bt\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "modpath = os.path.dirname(os.path.abspath(sys.argv[0]))\n",
+    "datapath = os.path.join(modpath, '../datas/yfinance')"
+   ]
+  },
+  {
+   "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>Date</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",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2023-06-20</td>\n",
+       "      <td>26841.664063</td>\n",
+       "      <td>28388.968750</td>\n",
+       "      <td>26668.791016</td>\n",
+       "      <td>28327.488281</td>\n",
+       "      <td>28327.488281</td>\n",
+       "      <td>22211859147</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2023-06-21</td>\n",
+       "      <td>28311.310547</td>\n",
+       "      <td>30737.330078</td>\n",
+       "      <td>28283.410156</td>\n",
+       "      <td>30027.296875</td>\n",
+       "      <td>30027.296875</td>\n",
+       "      <td>33346760979</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2023-06-22</td>\n",
+       "      <td>29995.935547</td>\n",
+       "      <td>30495.998047</td>\n",
+       "      <td>29679.158203</td>\n",
+       "      <td>29912.281250</td>\n",
+       "      <td>29912.281250</td>\n",
+       "      <td>20653160491</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2023-06-23</td>\n",
+       "      <td>29896.382813</td>\n",
+       "      <td>31389.539063</td>\n",
+       "      <td>29845.214844</td>\n",
+       "      <td>30695.468750</td>\n",
+       "      <td>30695.468750</td>\n",
+       "      <td>24115570085</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2023-06-24</td>\n",
+       "      <td>30708.738281</td>\n",
+       "      <td>30804.148438</td>\n",
+       "      <td>30290.146484</td>\n",
+       "      <td>30548.695313</td>\n",
+       "      <td>30548.695313</td>\n",
+       "      <td>12147822496</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         Date          Open          High           Low         Close  \\\n",
+       "0  2023-06-20  26841.664063  28388.968750  26668.791016  28327.488281   \n",
+       "1  2023-06-21  28311.310547  30737.330078  28283.410156  30027.296875   \n",
+       "2  2023-06-22  29995.935547  30495.998047  29679.158203  29912.281250   \n",
+       "3  2023-06-23  29896.382813  31389.539063  29845.214844  30695.468750   \n",
+       "4  2023-06-24  30708.738281  30804.148438  30290.146484  30548.695313   \n",
+       "\n",
+       "      Adj Close       Volume  \n",
+       "0  28327.488281  22211859147  \n",
+       "1  30027.296875  33346760979  \n",
+       "2  29912.281250  20653160491  \n",
+       "3  30695.468750  24115570085  \n",
+       "4  30548.695313  12147822496  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "btc = pd.read_csv('../datas/yfinance/BTC-USD.csv')\n",
+    "btc.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Date         datetime64[ns]\n",
+       "Open                float64\n",
+       "High                float64\n",
+       "Low                 float64\n",
+       "Close               float64\n",
+       "Adj Close           float64\n",
+       "Volume                int64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "btc['Date'] = pd.to_datetime(btc['Date'])\n",
+    "btc.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(Timestamp('2023-06-20 00:00:00'), Timestamp('2024-06-20 00:00:00'))"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "start_date = btc['Date'].min()\n",
+    "end_date = btc['Date'].max()\n",
+    "\n",
+    "start_date, end_date"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Initial plot"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "from mplfinance.original_flavor import candlestick_ohlc\n",
+    "import matplotlib.dates as mdates\n",
+    "\n",
+    "# Convert dates to Matplotlib date format\n",
+    "btc['Date'] = btc['Date'].apply(mdates.date2num)\n",
+    "ohlc = btc[['Date', 'Open', 'High', 'Low', 'Close', 'Volume']].values.tolist()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Create a figure and axis\n",
+    "fig, ax = plt.subplots()\n",
+    "\n",
+    "# Plot candlestick chart\n",
+    "candlestick_ohlc(ax, ohlc, width=0.6, colorup='g', colordown='r')\n",
+    "\n",
+    "# Format x-axis as dates\n",
+    "ax.xaxis_date()\n",
+    "ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))\n",
+    "\n",
+    "# Rotate x-axis labels for better readability\n",
+    "plt.xticks(rotation=45)\n",
+    "\n",
+    "# Set labels and title\n",
+    "plt.xlabel('Date')\n",
+    "plt.ylabel('Price')\n",
+    "plt.title('Bitcoin K-line Chart')\n",
+    "\n",
+    "# Display the plot\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Stratagys"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### simple stratagy\n",
+    "Buy at the opening price of each day and sell at the closing price of the day"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Initial Capital: $100000.00\n",
+      "Final Capital: $0.00\n",
+      "Returns: -100.00%\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "# Example Bitcoin K-line data (replace with your actual data)\n",
+    "btc = pd.DataFrame({\n",
+    "    'Date': ['2023-06-20', '2023-06-21', '2023-06-22', '2023-06-23', '2023-06-24'],\n",
+    "    'Open': [26841.664063, 28311.310547, 29995.935547, 29896.382813, 30708.738281],\n",
+    "    'Close': [28327.488281, 30027.296875, 29912.281250, 30695.468750, 30548.695313]\n",
+    "})\n",
+    "\n",
+    "initial_capital = 100000  # Example initial capital in USD\n",
+    "position = 0  # No initial position\n",
+    "capital = initial_capital\n",
+    "capital_over_time = [capital]\n",
+    "\n",
+    "for index, row in btc.iterrows():\n",
+    "    if position == 0:  # Buy condition\n",
+    "        position = capital / row['Open']\n",
+    "        capital = 0\n",
+    "    elif position > 0:  # Sell condition\n",
+    "        capital = position * row['Close']\n",
+    "        position = 0\n",
+    "    \n",
+    "    capital_over_time.append(capital)\n",
+    "\n",
+    "# Calculate final capital and returns\n",
+    "final_capital = capital\n",
+    "returns = (final_capital - initial_capital) / initial_capital * 100\n",
+    "\n",
+    "print(f'Initial Capital: ${initial_capital:.2f}')\n",
+    "print(f'Final Capital: ${final_capital:.2f}')\n",
+    "print(f'Returns: {returns:.2f}%')\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This highlights a crucial limitation of this approach."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1200x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plotting the capital over time\n",
+    "plt.figure(figsize=(12, 6))\n",
+    "plt.plot(capital_over_time, marker='o', linestyle='-', color='b', label='Capital')\n",
+    "plt.title('Capital Over Time')\n",
+    "plt.xlabel('Days')\n",
+    "plt.ylabel('Capital (USD)')\n",
+    "plt.xticks(range(len(btc)), btc['Date'], rotation=45)\n",
+    "plt.legend()\n",
+    "plt.grid(True)\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Genv",
+   "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": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/notebooks/backtrader.ipynb b/notebooks/backtrader.ipynb
deleted file mode 100644
index d473acc..0000000
--- a/notebooks/backtrader.ipynb
+++ /dev/null
@@ -1,166 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Feteching data from Yahoo finance"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import sys\n",
-    "import os\n",
-    "sys.path.append('../')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import yfinance as yf\n",
-    "import backtrader as bt\n",
-    "import pandas as pd\n",
-    "from datetime import datetime"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Fetching data from Binance"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from BinanceAPI import *\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import requests\n",
-    "import json\n",
-    "from datetime import datetime\n",
-    "\n",
-    "# Define the Binance API endpoint for Kline data\n",
-    "endpoint = 'https://api.binance.com/api/v3/klines'"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Parameters for the API request\n",
-    "symbol = 'BTCUSDT'  # Bitcoin against USDT\n",
-    "interval = '1h'     # 1 hour interval (other options: 1m, 5m, 15m, 1h, 4h, 1d, 1w)\n",
-    "limit = 1000        # Limit of data points to retrieve (max is 1000 per request)\n",
-    "\n",
-    "# Convert interval to milliseconds (Binance API expects it in milliseconds)\n",
-    "interval_ms = {\n",
-    "    '1m': 60000,\n",
-    "    '5m': 300000,\n",
-    "    '15m': 900000,\n",
-    "    '1h': 3600000,\n",
-    "    '4h': 14400000,\n",
-    "    '1d': 86400000,\n",
-    "    '1w': 604800000\n",
-    "}[interval]\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Convert start and end times to milliseconds\n",
-    "start_time = int(datetime.strptime('2020-01-01', '%Y-%m-%d').timestamp()) * 1000  # Example: start date\n",
-    "end_time = int(datetime.strptime('2024-01-01', '%Y-%m-%d').timestamp()) * 1000    # Example: end date\n",
-    "\n",
-    "# Prepare the parameters for the API request\n",
-    "params = {\n",
-    "    'symbol': symbol,\n",
-    "    'interval': interval,\n",
-    "    'startTime': start_time,\n",
-    "    'endTime': end_time,\n",
-    "    'limit': limit\n",
-    "}\n",
-    "\n",
-    "# Make the API request\n",
-    "response = requests.get(endpoint, params=params)\n",
-    "data = response.json()\n",
-    "\n",
-    "# Example of printing the fetched data\n",
-    "for candle in data:\n",
-    "    print(f\"Open time: {datetime.utcfromtimestamp(candle[0] / 1000)} \\\n",
-    "          Close time: {datetime.utcfromtimestamp(candle[6] / 1000)} \\\n",
-    "          Open: {candle[1]} \\\n",
-    "          Close: {candle[4]} \\\n",
-    "          High: {candle[2]} \\\n",
-    "          Low: {candle[3]} \\\n",
-    "          Volume: {candle[5]}\")\n",
-    "\n",
-    "# You can further process or save this data for backtesting\n"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Genv",
-   "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": "3.12.3"
-  }
- },
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-}