backtest.ipynb

{
 "cells": [
  {
   "attachments": {
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     "image/png": 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"
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"
    }
   },
   "cell_type": "markdown",
   "id": "2eb311ff-aa10-4590-8c94-740805e60375",
   "metadata": {},
   "source": [
    "# Order Block\n",
    "\n",
    "\n",
    "Pour qu'un order block soit valide il faut une FVG après cet orderblock + cassure du range ou retournement du range\n",
    "![image.png](attachment:2f3e60c7-db3e-43c1-bf25-9bb7ac0cfc0a.png)\n",
    "![image.png](attachment:266aa83e-94c0-46b2-b158-4333f91c11f6.png)\n",
    "\n",
    "https://youtu.be/4G2YYt73mgo?t=396"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2656481-12ef-457d-a6ab-530f9eeae3c5",
   "metadata": {},
   "source": [
    "# Importation des modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "a1407f50-1b98-451f-aa89-5c70efb82213",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import pandas_ta as ta\n",
    "import matplotlib.pyplot as plt\n",
    "import plotly.graph_objects as go\n",
    "import plotly.io as pio\n",
    "import numpy as np\n",
    "from tqdm import tqdm\n",
    "import matplotlib\n",
    "matplotlib.use('TkAgg')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67774f16-752f-4c40-b990-d81b39548fbb",
   "metadata": {},
   "source": [
    "# Importation des datas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "7b8002c0-7eec-4655-8088-ab7152a88ef7",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv('USDJPY_M15.csv')\n",
    "data.columns = ['date', 'open', 'high', 'low', 'close', 'volume']\n",
    "data['date'] = pd.to_datetime(data['date'])\n",
    "data = data.set_index(['date'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "f23fc866-ead1-4ee5-98cf-32aabb75184e",
   "metadata": {},
   "outputs": [],
   "source": [
    "data['ohlc4'] = (data['open'] + data['high'] + data['low'] + data['close']) / 4 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "a7f0087f-9b35-427c-adfb-0b3ae4b4dc8c",
   "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>volume</th>\n",
       "      <th>ohlc4</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>2020-09-17 17:00:00</th>\n",
       "      <td>104.830</td>\n",
       "      <td>104.841</td>\n",
       "      <td>104.801</td>\n",
       "      <td>104.805</td>\n",
       "      <td>742</td>\n",
       "      <td>104.81925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-17 17:15:00</th>\n",
       "      <td>104.805</td>\n",
       "      <td>104.807</td>\n",
       "      <td>104.779</td>\n",
       "      <td>104.781</td>\n",
       "      <td>656</td>\n",
       "      <td>104.79300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-17 17:30:00</th>\n",
       "      <td>104.781</td>\n",
       "      <td>104.786</td>\n",
       "      <td>104.771</td>\n",
       "      <td>104.777</td>\n",
       "      <td>335</td>\n",
       "      <td>104.77875</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-17 17:45:00</th>\n",
       "      <td>104.777</td>\n",
       "      <td>104.777</td>\n",
       "      <td>104.755</td>\n",
       "      <td>104.758</td>\n",
       "      <td>553</td>\n",
       "      <td>104.76675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-17 18:00:00</th>\n",
       "      <td>104.757</td>\n",
       "      <td>104.787</td>\n",
       "      <td>104.724</td>\n",
       "      <td>104.724</td>\n",
       "      <td>1203</td>\n",
       "      <td>104.74800</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>2024-09-19 15:45:00</th>\n",
       "      <td>142.941</td>\n",
       "      <td>142.974</td>\n",
       "      <td>142.867</td>\n",
       "      <td>142.883</td>\n",
       "      <td>4771</td>\n",
       "      <td>142.91625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-19 16:00:00</th>\n",
       "      <td>142.882</td>\n",
       "      <td>143.031</td>\n",
       "      <td>142.854</td>\n",
       "      <td>143.005</td>\n",
       "      <td>4610</td>\n",
       "      <td>142.94300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-19 16:15:00</th>\n",
       "      <td>143.004</td>\n",
       "      <td>143.035</td>\n",
       "      <td>142.886</td>\n",
       "      <td>142.937</td>\n",
       "      <td>3384</td>\n",
       "      <td>142.96550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-19 16:30:00</th>\n",
       "      <td>142.938</td>\n",
       "      <td>143.133</td>\n",
       "      <td>142.909</td>\n",
       "      <td>143.103</td>\n",
       "      <td>4978</td>\n",
       "      <td>143.02075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-19 16:45:00</th>\n",
       "      <td>143.102</td>\n",
       "      <td>143.108</td>\n",
       "      <td>142.999</td>\n",
       "      <td>143.035</td>\n",
       "      <td>9830</td>\n",
       "      <td>143.06100</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>99999 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        open     high      low    close  volume      ohlc4\n",
       "date                                                                      \n",
       "2020-09-17 17:00:00  104.830  104.841  104.801  104.805     742  104.81925\n",
       "2020-09-17 17:15:00  104.805  104.807  104.779  104.781     656  104.79300\n",
       "2020-09-17 17:30:00  104.781  104.786  104.771  104.777     335  104.77875\n",
       "2020-09-17 17:45:00  104.777  104.777  104.755  104.758     553  104.76675\n",
       "2020-09-17 18:00:00  104.757  104.787  104.724  104.724    1203  104.74800\n",
       "...                      ...      ...      ...      ...     ...        ...\n",
       "2024-09-19 15:45:00  142.941  142.974  142.867  142.883    4771  142.91625\n",
       "2024-09-19 16:00:00  142.882  143.031  142.854  143.005    4610  142.94300\n",
       "2024-09-19 16:15:00  143.004  143.035  142.886  142.937    3384  142.96550\n",
       "2024-09-19 16:30:00  142.938  143.133  142.909  143.103    4978  143.02075\n",
       "2024-09-19 16:45:00  143.102  143.108  142.999  143.035    9830  143.06100\n",
       "\n",
       "[99999 rows x 6 columns]"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e01a1e1-42f3-4b79-9a83-2d2bd285b2f9",
   "metadata": {},
   "source": [
    "# Détection des FVGs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "48d96524-80d7-4ca8-b7b7-decb9eed4761",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 99997/99997 [00:21<00:00, 4676.99it/s]\n"
     ]
    }
   ],
   "source": [
    "# fvg calculation\n",
    "window = 3\n",
    "fvgs = np.zeros((len(data), 2))\n",
    "last_fvg_up = data['ohlc4'].iloc[0]\n",
    "last_fvg_down = data['ohlc4'].iloc[0]\n",
    "fvgs[:window] = last_fvg_up\n",
    "for i in tqdm(range(window, len(data)+1)):\n",
    "    rows = data.iloc[i-window:i]\n",
    "    if rows['open'].iloc[0] > rows['close'].iloc[2]:\n",
    "        if rows['low'].iloc[0] > rows['high'].iloc[2]:\n",
    "            last_fvg_up = rows['low'].iloc[0]\n",
    "            last_fvg_down = rows['high'].iloc[2]\n",
    "    if rows['open'].iloc[0] < rows['close'].iloc[2]:\n",
    "        if rows['high'].iloc[0] < rows['low'].iloc[2]:\n",
    "            last_fvg_up = rows['low'].iloc[2]\n",
    "            last_fvg_down = rows['high'].iloc[0]\n",
    "\n",
    "    fvgs[i-1, 0] = last_fvg_down\n",
    "    fvgs[i-1, 1] = last_fvg_up"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9caa3cd7-860c-48be-a37c-2274c5921635",
   "metadata": {},
   "source": [
    "# Détection des TOP/BOTTOM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "b95dcf1c-b55b-4438-a126-6ae8f70b822c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 99958/99958 [00:08<00:00, 11689.62it/s]\n"
     ]
    }
   ],
   "source": [
    "neighborhoods = 20\n",
    "window = neighborhoods * 2 + 1\n",
    "last_top = data['ohlc4'].iloc[0]\n",
    "last_bottom = data['ohlc4'].iloc[0]\n",
    "top_bottom_df = []\n",
    "index_top = []\n",
    "index_bottom = []\n",
    "for i in tqdm(range(window, len(data))):\n",
    "    row = data.iloc[i - window:i]\n",
    "    price = list(row['ohlc4'])\n",
    "    midle_point = price.pop(-neighborhoods-1)\n",
    "    if all(neighborhood < midle_point for neighborhood in price):\n",
    "        last_top = midle_point\n",
    "        index_top.append(i-1-neighborhoods)\n",
    "    elif all(neighborhood > midle_point for neighborhood in price):\n",
    "        last_bottom = midle_point\n",
    "        index_bottom.append(i-1-neighborhoods)\n",
    "    top_bottom_df.append([last_top, last_bottom]) "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "247ed769-443b-4a9d-b9af-e674c8986167",
   "metadata": {},
   "source": [
    "# Avec les TOP/BOTTOM on peut trouver nos breakers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "62dda597-17fa-4779-94a5-41e9a89544ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "dates_top = data['ohlc4'].index[index_top]\n",
    "prices_top = data['ohlc4'].iloc[index_top].values  # Convertir en numpy array pour éviter les conflits d'index\n",
    "\n",
    "dates_bottom = data['ohlc4'].index[index_bottom]\n",
    "prices_bottom = data['ohlc4'].iloc[index_bottom].values  # Convertir en numpy array pour éviter les conflits d'index\n",
    "\n",
    "# Créer des DataFrames pour les tops et bottoms\n",
    "df_tops = pd.DataFrame({\n",
    "    'date': dates_top,\n",
    "    'price': prices_top,\n",
    "    'type': 'top'\n",
    "})\n",
    "\n",
    "df_bottoms = pd.DataFrame({\n",
    "    'date': dates_bottom,\n",
    "    'price': prices_bottom,\n",
    "    'type': 'bottom'\n",
    "})\n",
    "\n",
    "# Combiner et trier les points par date\n",
    "df_points = pd.concat([df_tops, df_bottoms], ignore_index=True).sort_values('date').reset_index(drop=True)\n",
    "\n",
    "# Créer le graphique\n",
    "plt.figure(figsize=(14, 7))\n",
    "plt.plot(data['ohlc4'].index, data['ohlc4'].values, label='Prix')\n",
    "\n",
    "# Ajouter les points tops et bottoms\n",
    "plt.scatter(df_tops['date'], df_tops['price'], color='green', marker='^', label='Tops')\n",
    "plt.scatter(df_bottoms['date'], df_bottoms['price'], color='red', marker='v', label='Bottoms')\n",
    "\n",
    "# Connecter les points en alternant entre tops et bottoms\n",
    "for i in range(len(df_points) - 1):\n",
    "    date_current = df_points.loc[i, 'date']\n",
    "    price_current = df_points.loc[i, 'price']\n",
    "    date_next = df_points.loc[i + 1, 'date']\n",
    "    price_next = df_points.loc[i + 1, 'price']\n",
    "    plt.plot([date_current, date_next], [price_current, price_next], color='black', linestyle='--')\n",
    "\n",
    "plt.legend()\n",
    "plt.title('Prix avec Tops et Bottoms Connectés')\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Prix')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "57d4f9b9-cf0a-4ada-88f6-0a3e3b693120",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 98999/98999 [01:56<00:00, 849.26it/s] \n"
     ]
    }
   ],
   "source": [
    "# orderblock calculation\n",
    "window_detection = 1000\n",
    "df_window_points = df_points.set_index(['date']).reindex(data.index).shift(neighborhoods).ffill()\n",
    "\n",
    "buy_breaker_block_low = data['ohlc4'].iloc[0]\n",
    "buy_breaker_block_high = data['ohlc4'].iloc[0]\n",
    "sell_breaker_block_low = data['ohlc4'].iloc[0]\n",
    "sell_breaker_block_high = data['ohlc4'].iloc[0]\n",
    "breaker_block_df = [[data['ohlc4'].iloc[0]] * 4] * window_detection\n",
    "# Boucle sur la plage de données\n",
    "for window in tqdm(range(window_detection, len(data))):\n",
    "    # Extraction des données pour la fenêtre actuelle\n",
    "    data_row = data.iloc[window - window_detection: window]\n",
    "    row_points = df_window_points.iloc[window - window_detection: window]\n",
    "    # Suppression des doublons basés sur 'price' et 'type'\n",
    "    row_points = row_points.drop_duplicates(subset=['price', 'type'], keep='first')\n",
    "    \n",
    "    # Vérification si nous avons au moins 4 points\n",
    "    if len(row_points) < 4:\n",
    "        breaker_block_df.append([buy_breaker_block_low, buy_breaker_block_high, sell_breaker_block_low, sell_breaker_block_high])\n",
    "        continue\n",
    "    else:\n",
    "        # Sélection des 4 derniers points\n",
    "        last_points = row_points.copy().iloc[-4:]\n",
    "        \n",
    "        # Conditions pour le breaker block haussier\n",
    "        bull_pattern_cond = (\n",
    "            (last_points['type'].iloc[0] == 'bottom') and\n",
    "            (last_points['type'].iloc[1] == 'top') and\n",
    "            (last_points['type'].iloc[2] == 'bottom') and\n",
    "            (last_points['type'].iloc[3] == 'top')\n",
    "        )\n",
    "        \n",
    "        # Conditions pour le breaker block baissier\n",
    "        bear_pattern_cond = (\n",
    "            (last_points['type'].iloc[0] == 'top') and\n",
    "            (last_points['type'].iloc[1] == 'bottom') and\n",
    "            (last_points['type'].iloc[2] == 'top') and\n",
    "            (last_points['type'].iloc[3] == 'bottom')\n",
    "        )\n",
    "        \n",
    "        # Extraction des prix correspondants aux derniers points\n",
    "        price_points = last_points['price'].reset_index(drop=True)\n",
    "        \n",
    "        # Détection du breaker block haussier\n",
    "        if bull_pattern_cond:\n",
    "            cond1buy = price_points.iloc[0] < price_points.iloc[1]\n",
    "            cond2buy = price_points.iloc[2] < price_points.iloc[0]\n",
    "            cond3buy = price_points.iloc[3] > price_points.iloc[1]\n",
    "            total_cond_buy = cond1buy and cond2buy and cond3buy\n",
    "            if total_cond_buy:\n",
    "                buy_breaker_block_low = price_points.iloc[0]\n",
    "                buy_breaker_block_high = price_points.iloc[1]\n",
    "        \n",
    "        # Détection du breaker block baissier\n",
    "        if bear_pattern_cond:\n",
    "            cond1sell = price_points.iloc[0] > price_points.iloc[1]\n",
    "            cond2sell = price_points.iloc[2] > price_points.iloc[0]\n",
    "            cond3sell = price_points.iloc[3] < price_points.iloc[1]\n",
    "            total_cond_sell = cond1sell and cond2sell and cond3sell\n",
    "            if total_cond_sell:\n",
    "                sell_breaker_block_high = price_points.iloc[0]\n",
    "                sell_breaker_block_low = price_points.iloc[1]\n",
    "    \n",
    "    # Ajout des résultats à la liste\n",
    "    breaker_block_df.append([\n",
    "        buy_breaker_block_low, \n",
    "        buy_breaker_block_high, \n",
    "        sell_breaker_block_low, \n",
    "        sell_breaker_block_high\n",
    "    ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "2d9e590f-6278-44d0-8b7c-019e2972ccef",
   "metadata": {},
   "outputs": [],
   "source": [
    "data[['fvg_down', 'fvg_up']] = fvgs\n",
    "data[['buy_breaker_block_low', 'buy_breaker_block_high', 'sell_breaker_block_low', 'sell_breaker_block_high']] = np.array(breaker_block_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "f97bfbf2-2648-4627-9f1b-7b10977c2adc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>buy_breaker_block_low</th>\n",
       "      <th>buy_breaker_block_high</th>\n",
       "      <th>sell_breaker_block_low</th>\n",
       "      <th>sell_breaker_block_high</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-09-17 17:00:00</th>\n",
       "      <td>104.81925</td>\n",
       "      <td>104.81925</td>\n",
       "      <td>104.81925</td>\n",
       "      <td>104.81925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-17 17:15:00</th>\n",
       "      <td>104.81925</td>\n",
       "      <td>104.81925</td>\n",
       "      <td>104.81925</td>\n",
       "      <td>104.81925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-17 17:30:00</th>\n",
       "      <td>104.81925</td>\n",
       "      <td>104.81925</td>\n",
       "      <td>104.81925</td>\n",
       "      <td>104.81925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-17 17:45:00</th>\n",
       "      <td>104.81925</td>\n",
       "      <td>104.81925</td>\n",
       "      <td>104.81925</td>\n",
       "      <td>104.81925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-17 18:00:00</th>\n",
       "      <td>104.81925</td>\n",
       "      <td>104.81925</td>\n",
       "      <td>104.81925</td>\n",
       "      <td>104.81925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-19 15:45:00</th>\n",
       "      <td>140.45250</td>\n",
       "      <td>140.93550</td>\n",
       "      <td>144.31075</td>\n",
       "      <td>144.59775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-19 16:00:00</th>\n",
       "      <td>140.45250</td>\n",
       "      <td>140.93550</td>\n",
       "      <td>144.31075</td>\n",
       "      <td>144.59775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-19 16:15:00</th>\n",
       "      <td>140.45250</td>\n",
       "      <td>140.93550</td>\n",
       "      <td>144.31075</td>\n",
       "      <td>144.59775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-19 16:30:00</th>\n",
       "      <td>140.45250</td>\n",
       "      <td>140.93550</td>\n",
       "      <td>144.31075</td>\n",
       "      <td>144.59775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-19 16:45:00</th>\n",
       "      <td>140.45250</td>\n",
       "      <td>140.93550</td>\n",
       "      <td>144.31075</td>\n",
       "      <td>144.59775</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>99999 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     buy_breaker_block_low  buy_breaker_block_high  \\\n",
       "date                                                                 \n",
       "2020-09-17 17:00:00              104.81925               104.81925   \n",
       "2020-09-17 17:15:00              104.81925               104.81925   \n",
       "2020-09-17 17:30:00              104.81925               104.81925   \n",
       "2020-09-17 17:45:00              104.81925               104.81925   \n",
       "2020-09-17 18:00:00              104.81925               104.81925   \n",
       "...                                    ...                     ...   \n",
       "2024-09-19 15:45:00              140.45250               140.93550   \n",
       "2024-09-19 16:00:00              140.45250               140.93550   \n",
       "2024-09-19 16:15:00              140.45250               140.93550   \n",
       "2024-09-19 16:30:00              140.45250               140.93550   \n",
       "2024-09-19 16:45:00              140.45250               140.93550   \n",
       "\n",
       "                     sell_breaker_block_low  sell_breaker_block_high  \n",
       "date                                                                  \n",
       "2020-09-17 17:00:00               104.81925                104.81925  \n",
       "2020-09-17 17:15:00               104.81925                104.81925  \n",
       "2020-09-17 17:30:00               104.81925                104.81925  \n",
       "2020-09-17 17:45:00               104.81925                104.81925  \n",
       "2020-09-17 18:00:00               104.81925                104.81925  \n",
       "...                                     ...                      ...  \n",
       "2024-09-19 15:45:00               144.31075                144.59775  \n",
       "2024-09-19 16:00:00               144.31075                144.59775  \n",
       "2024-09-19 16:15:00               144.31075                144.59775  \n",
       "2024-09-19 16:30:00               144.31075                144.59775  \n",
       "2024-09-19 16:45:00               144.31075                144.59775  \n",
       "\n",
       "[99999 rows x 4 columns]"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[['buy_breaker_block_low', 'buy_breaker_block_high', 'sell_breaker_block_low', 'sell_breaker_block_high']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "a9066988-7d77-4f01-a06d-ef25c09d055d",
   "metadata": {},
   "outputs": [],
   "source": [
    "size = 2000\n",
    "range_rand = int(np.random.uniform(low=0, high=len(data)-size))\n",
    "sample = data.iloc[range_rand:range_rand+size]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "892cf285-20a3-402e-b34d-3242993822a0",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_bottoms_sample = df_bottoms[(df_bottoms['date'] >= sample.index.min()) & (df_bottoms['date'] <= sample.index.max())]\n",
    "df_tops_sample = df_tops[(df_tops['date'] >= sample.index.min()) & (df_tops['date'] <= sample.index.max())]\n",
    "df_points_sample = df_points[(df_points['date'] >= sample.index.min()) & (df_points['date'] <= sample.index.max())]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "01cac428-0839-4cf8-9b8f-1b03f5ef3c8f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import plotly.graph_objects as go\n",
    "import plotly.io as pio\n",
    "\n",
    "fig = go.Figure()\n",
    "\n",
    "# Ajouter le chandelier en utilisant un axe catégoriel\n",
    "fig.add_trace(go.Candlestick(\n",
    "    x=sample.index,  # Utilisation des dates sous forme d'index (axe catégoriel)\n",
    "    open=sample['open'],\n",
    "    high=sample['high'],\n",
    "    low=sample['low'],\n",
    "    close=sample['close'],\n",
    "    name='Chandelier'\n",
    "))\n",
    "\n",
    "# Ajouter les bandes de Bollinger\n",
    "fig.add_trace(go.Scatter(\n",
    "    x=sample.index,\n",
    "    y=sample['fvg_down'],\n",
    "    line=dict(color='blue', width=1),\n",
    "    name='fvg Bande inférieure',\n",
    "    mode='lines'\n",
    "))\n",
    "\n",
    "fig.add_trace(go.Scatter(\n",
    "    x=sample.index,\n",
    "    y=sample['fvg_up'],\n",
    "    line=dict(color='blue', width=1),\n",
    "    fill='tonexty',  # Remplir entre les bandes\n",
    "    name='fvg Bande supérieure',\n",
    "    mode='lines'\n",
    "))\n",
    "\n",
    "# Ajouter les Breaker Blocks haussiers (Bullish)\n",
    "fig.add_trace(go.Scatter(\n",
    "    x=sample.index,\n",
    "    y=sample['buy_breaker_block_low'],\n",
    "    line=dict(color='green', width=1),\n",
    "    name='BB Bullish Bas',\n",
    "    mode='lines'\n",
    "))\n",
    "\n",
    "fig.add_trace(go.Scatter(\n",
    "    x=sample.index,\n",
    "    y=sample['buy_breaker_block_high'],\n",
    "    line=dict(color='green', width=1),\n",
    "    fill='tonexty',  # Remplir entre les bandes\n",
    "    name='BB Bullish Haut',\n",
    "    mode='lines'\n",
    "))\n",
    "\n",
    "# Ajouter les Breaker Blocks baissiers (Bearish)\n",
    "fig.add_trace(go.Scatter(\n",
    "    x=sample.index,\n",
    "    y=sample['sell_breaker_block_low'],\n",
    "    line=dict(color='red', width=1),\n",
    "    name='BB Bearish Bas',\n",
    "    mode='lines'\n",
    "))\n",
    "\n",
    "fig.add_trace(go.Scatter(\n",
    "    x=sample.index,\n",
    "    y=sample['sell_breaker_block_high'],\n",
    "    line=dict(color='red', width=1),\n",
    "    fill='tonexty',  # Remplir entre les bandes\n",
    "    name='BB Bearish Haut',\n",
    "    mode='lines'\n",
    "))\n",
    "\n",
    "# Ajouter les points tops\n",
    "fig.add_trace(go.Scatter(\n",
    "    x=df_tops_sample['date'],\n",
    "    y=df_tops_sample['price'],\n",
    "    mode='markers',\n",
    "    marker=dict(symbol='triangle-up', color='green', size=10),\n",
    "    name='Tops'\n",
    "))\n",
    "\n",
    "# Ajouter les points bottoms\n",
    "fig.add_trace(go.Scatter(\n",
    "    x=df_bottoms_sample['date'],\n",
    "    y=df_bottoms_sample['price'],\n",
    "    mode='markers',\n",
    "    marker=dict(symbol='triangle-down', color='red', size=10),\n",
    "    name='Bottoms'\n",
    "))\n",
    "\n",
    "# Connecter les points tops et bottoms avec des lignes noires\n",
    "fig.add_trace(go.Scatter(\n",
    "    x=df_points_sample['date'],\n",
    "    y=df_points_sample['price'],\n",
    "    mode='lines',\n",
    "    line=dict(color='black', dash='dash'),\n",
    "    name='Lignes de connexion'\n",
    "))\n",
    "\n",
    "# Mettre en forme le graphique\n",
    "fig.update_layout(\n",
    "    title='Graphique Chandelier avec Tops et Bottoms Connectés',\n",
    "    xaxis_title='Date',\n",
    "    yaxis_title='Prix',\n",
    "    xaxis_rangeslider_visible=False,  # Cacher le slider par défaut\n",
    "    xaxis_type='category',  # Configurer l'axe des X en catégoriel\n",
    "    template='plotly_white'\n",
    ")\n",
    "\n",
    "# Afficher le graphique dans une nouvelle fenêtre de navigateur\n",
    "pio.renderers.default = \"browser\"\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fbdb2136-392a-467c-974d-ee353dc7f335",
   "metadata": {},
   "source": [
    "# Logique du backtest"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c54bf83-d95d-4fe3-9f2f-620abb6e1755",
   "metadata": {},
   "source": [
    "# ⚠️ Avertissement\n",
    "\n",
    "Lorsque vous réduisez le **stop loss** vers zéro dans votre stratégie de trading, cela peut entraîner des résultats **irréalistes** et potentiellement dangereux :\n",
    "\n",
    "- **Take Profit et Stop Loss au niveau du prix d'entrée :**\n",
    "  - Avec un stop loss proche de zéro, le stop loss et le take profit sont pratiquement égaux au **prix d'entrée**.\n",
    "  - De **minuscules fluctuations** du marché peuvent déclencher le take profit, donnant l'illusion de gains faciles.\n",
    "\n",
    "- **PNL artificiellement élevé :**\n",
    "  - Les petits gains répétés sans pertes apparentes peuvent s'accumuler, créant un **PNL total énorme**.\n",
    "  - Cela **ne reflète pas la réalité** des conditions du marché et peut conduire à une **fausse confiance** dans la stratégie.\n",
    "\n",
    "- **Absence de trades perdants :**\n",
    "  - Un stop loss à zéro signifie que le stop loss n'est **presque jamais déclenché**, éliminant les pertes dans la simulation.\n",
    "  - Cela **biaisera** vos résultats et vous empêchera d'évaluer correctement les risques.\n",
    "\n",
    "- **Ignoration des coûts de transaction :**\n",
    "  - Les **frais**, le **slippage** et le **spread** ne sont pas pris en compte, ce qui est crucial pour une stratégie avec une fréquence de trading élevée.\n",
    "  - Ces coûts peuvent **annuler les petits gains** réalisés sur chaque trade.\n",
    "\n",
    "## **Recommandations :**\n",
    "\n",
    "- **Ne pas définir le stop loss à zéro :**\n",
    "  - Fixez un stop loss minimal réaliste (par exemple, **0,5% ou 1%**) pour refléter les conditions du marché.\n",
    "\n",
    "- **Inclure les coûts de transaction :**\n",
    "  - Intégrez les **frais de trading**, le **slippage** et le **spread** dans votre simulation pour des résultats plus précis.\n",
    "\n",
    "- **Limiter la fréquence des trades :**\n",
    "  - Évitez d'entrer et de sortir de positions sur des **fluctuations de prix insignifiantes**.\n",
    "\n",
    "- **Vérifier les données utilisées :**\n",
    "  - Assurez-vous que vos données de prix sont **précises et granulaires** pour éviter des déclenchements irréalistes du stop loss ou du take profit.\n",
    "\n",
    "---\n",
    "\n",
    "**Attention :** Ignorer ces points peut conduire à une **mauvaise évaluation des risques** et à des **pertes financières importantes** lors de l'application de la stratégie en conditions réelles."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "9be230ce-78df-4253-998f-1e076bb9de0c",
   "metadata": {},
   "outputs": [],
   "source": [
    "in_pos = None\n",
    "stop_loss = 0.005\n",
    "rr = 4\n",
    "strat_logs = []\n",
    "\n",
    "for index, row in data.iterrows():\n",
    "    if in_pos == 'long':\n",
    "        if row.ohlc4 <= actual_stop:\n",
    "            # Stop loss atteint\n",
    "            exit_price = actual_stop\n",
    "            exit_time = index\n",
    "            pnl = exit_price - entry_price\n",
    "            strat_logs.append([exit_price, entry_price, in_pos, entry_time, exit_time, pnl])\n",
    "            in_pos = None\n",
    "        elif row.ohlc4 >= take_profit:\n",
    "            # Take profit atteint\n",
    "            exit_price = take_profit\n",
    "            exit_time = index\n",
    "            pnl = exit_price - entry_price\n",
    "            strat_logs.append([exit_price, entry_price, in_pos, entry_time, exit_time, pnl])\n",
    "            in_pos = None\n",
    "    elif in_pos == 'short':\n",
    "        if row.ohlc4 >= actual_stop:\n",
    "            # Stop loss atteint\n",
    "            exit_price = actual_stop\n",
    "            exit_time = index\n",
    "            pnl = entry_price - exit_price\n",
    "            strat_logs.append([exit_price, entry_price, in_pos, entry_time, exit_time, pnl])\n",
    "            in_pos = None\n",
    "        elif row.ohlc4 <= take_profit:\n",
    "            # Take profit atteint\n",
    "            exit_price = take_profit\n",
    "            exit_time = index\n",
    "            pnl = entry_price - exit_price\n",
    "            strat_logs.append([exit_price, entry_price, in_pos, entry_time, exit_time, pnl])\n",
    "            in_pos = None\n",
    "    else:\n",
    "        # Pas en position\n",
    "        if row.ohlc4 > row.fvg_down and row.ohlc4 < row.fvg_up:\n",
    "            if row.ohlc4 > row.buy_breaker_block_low and row.ohlc4 < row.buy_breaker_block_high:\n",
    "                # Entrée en position longue\n",
    "                in_pos = 'long'\n",
    "                entry_price = row.ohlc4\n",
    "                actual_stop = entry_price * (1 - stop_loss)\n",
    "                stop_distance = entry_price - actual_stop\n",
    "                take_profit = entry_price + stop_distance * rr\n",
    "                entry_time = index\n",
    "            elif row.ohlc4 > row.sell_breaker_block_low and row.ohlc4 < row.sell_breaker_block_high:\n",
    "                # Entrée en position courte\n",
    "                in_pos = 'short'\n",
    "                entry_price = row.ohlc4\n",
    "                actual_stop = entry_price * (1 + stop_loss)\n",
    "                stop_distance = actual_stop - entry_price\n",
    "                take_profit = entry_price - stop_distance * rr\n",
    "                entry_time = index\n",
    "\n",
    "strat_logs = pd.DataFrame(strat_logs, columns=['exit_price', 'entry_price', 'type', 'entry_time', 'exit_time', 'pnl'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "457270f1-f3ed-4f74-b189-928da6bb1f11",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.title(\"USDJPY / SL 0.5% / RR 4\")\n",
    "strat_logs['pnl'].cumsum().plot(figsize=(12,8))\n",
    "plt.xlabel(\"Nombre de Trades\")\n",
    "plt.ylabel(\"PnL\")\n",
    "plt.savefig(\"USDJPY SL 0.5% RR 4.png\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "5ca65659-01bd-4379-91ef-bed601924f43",
   "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>exit_price</th>\n",
       "      <th>entry_price</th>\n",
       "      <th>type</th>\n",
       "      <th>entry_time</th>\n",
       "      <th>exit_time</th>\n",
       "      <th>pnl</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>838</th>\n",
       "      <td>1.085511</td>\n",
       "      <td>1.085403</td>\n",
       "      <td>short</td>\n",
       "      <td>2024-05-27 13:30:00</td>\n",
       "      <td>2024-05-27 13:45:00</td>\n",
       "      <td>-0.000109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>839</th>\n",
       "      <td>1.085966</td>\n",
       "      <td>1.086075</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-05-27 16:45:00</td>\n",
       "      <td>2024-05-27 17:00:00</td>\n",
       "      <td>-0.000109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>840</th>\n",
       "      <td>1.085884</td>\n",
       "      <td>1.085993</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-05-28 19:30:00</td>\n",
       "      <td>2024-05-28 20:30:00</td>\n",
       "      <td>-0.000109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>841</th>\n",
       "      <td>1.085659</td>\n",
       "      <td>1.085767</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-05-28 21:15:00</td>\n",
       "      <td>2024-05-28 22:30:00</td>\n",
       "      <td>-0.000109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>842</th>\n",
       "      <td>1.085449</td>\n",
       "      <td>1.085340</td>\n",
       "      <td>short</td>\n",
       "      <td>2024-06-03 02:30:00</td>\n",
       "      <td>2024-06-03 03:00:00</td>\n",
       "      <td>-0.000109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>843</th>\n",
       "      <td>1.084693</td>\n",
       "      <td>1.085453</td>\n",
       "      <td>short</td>\n",
       "      <td>2024-06-03 03:15:00</td>\n",
       "      <td>2024-06-03 07:45:00</td>\n",
       "      <td>0.000760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>844</th>\n",
       "      <td>1.087226</td>\n",
       "      <td>1.086465</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-06-04 12:00:00</td>\n",
       "      <td>2024-06-04 14:45:00</td>\n",
       "      <td>0.000761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>845</th>\n",
       "      <td>1.087368</td>\n",
       "      <td>1.086608</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-06-05 11:45:00</td>\n",
       "      <td>2024-06-05 12:15:00</td>\n",
       "      <td>0.000761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>846</th>\n",
       "      <td>1.073248</td>\n",
       "      <td>1.073355</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-06-24 22:45:00</td>\n",
       "      <td>2024-06-24 23:00:00</td>\n",
       "      <td>-0.000107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>847</th>\n",
       "      <td>1.074349</td>\n",
       "      <td>1.073597</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-06-30 22:45:00</td>\n",
       "      <td>2024-07-01 00:30:00</td>\n",
       "      <td>0.000752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>848</th>\n",
       "      <td>1.073895</td>\n",
       "      <td>1.074002</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-07-01 20:45:00</td>\n",
       "      <td>2024-07-01 21:00:00</td>\n",
       "      <td>-0.000107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>849</th>\n",
       "      <td>1.073798</td>\n",
       "      <td>1.073905</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-07-01 22:00:00</td>\n",
       "      <td>2024-07-01 22:45:00</td>\n",
       "      <td>-0.000107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>850</th>\n",
       "      <td>1.073383</td>\n",
       "      <td>1.073490</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-07-02 14:45:00</td>\n",
       "      <td>2024-07-02 16:15:00</td>\n",
       "      <td>-0.000107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>851</th>\n",
       "      <td>1.074139</td>\n",
       "      <td>1.073387</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-07-02 17:00:00</td>\n",
       "      <td>2024-07-02 18:15:00</td>\n",
       "      <td>0.000751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>852</th>\n",
       "      <td>1.074589</td>\n",
       "      <td>1.073837</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-07-03 05:30:00</td>\n",
       "      <td>2024-07-03 07:00:00</td>\n",
       "      <td>0.000752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>853</th>\n",
       "      <td>1.082788</td>\n",
       "      <td>1.082680</td>\n",
       "      <td>short</td>\n",
       "      <td>2024-07-08 03:00:00</td>\n",
       "      <td>2024-07-08 03:15:00</td>\n",
       "      <td>-0.000108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>854</th>\n",
       "      <td>1.082593</td>\n",
       "      <td>1.082485</td>\n",
       "      <td>short</td>\n",
       "      <td>2024-07-09 02:30:00</td>\n",
       "      <td>2024-07-09 02:45:00</td>\n",
       "      <td>-0.000108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>855</th>\n",
       "      <td>1.082078</td>\n",
       "      <td>1.081970</td>\n",
       "      <td>short</td>\n",
       "      <td>2024-07-09 08:30:00</td>\n",
       "      <td>2024-07-09 08:45:00</td>\n",
       "      <td>-0.000108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>856</th>\n",
       "      <td>1.081873</td>\n",
       "      <td>1.081765</td>\n",
       "      <td>short</td>\n",
       "      <td>2024-07-09 13:00:00</td>\n",
       "      <td>2024-07-09 13:15:00</td>\n",
       "      <td>-0.000108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>857</th>\n",
       "      <td>1.082068</td>\n",
       "      <td>1.081960</td>\n",
       "      <td>short</td>\n",
       "      <td>2024-07-10 04:00:00</td>\n",
       "      <td>2024-07-10 07:00:00</td>\n",
       "      <td>-0.000108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>858</th>\n",
       "      <td>1.082041</td>\n",
       "      <td>1.081932</td>\n",
       "      <td>short</td>\n",
       "      <td>2024-07-10 09:45:00</td>\n",
       "      <td>2024-07-10 10:30:00</td>\n",
       "      <td>-0.000108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>859</th>\n",
       "      <td>1.082473</td>\n",
       "      <td>1.082365</td>\n",
       "      <td>short</td>\n",
       "      <td>2024-07-10 15:00:00</td>\n",
       "      <td>2024-07-10 15:15:00</td>\n",
       "      <td>-0.000108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>860</th>\n",
       "      <td>1.082496</td>\n",
       "      <td>1.082387</td>\n",
       "      <td>short</td>\n",
       "      <td>2024-07-10 16:00:00</td>\n",
       "      <td>2024-07-10 16:15:00</td>\n",
       "      <td>-0.000108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>861</th>\n",
       "      <td>1.082168</td>\n",
       "      <td>1.082060</td>\n",
       "      <td>short</td>\n",
       "      <td>2024-07-10 18:30:00</td>\n",
       "      <td>2024-07-10 18:45:00</td>\n",
       "      <td>-0.000108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>862</th>\n",
       "      <td>1.088484</td>\n",
       "      <td>1.088593</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-07-22 06:00:00</td>\n",
       "      <td>2024-07-22 06:15:00</td>\n",
       "      <td>-0.000109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>863</th>\n",
       "      <td>1.088456</td>\n",
       "      <td>1.088565</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-07-22 06:30:00</td>\n",
       "      <td>2024-07-22 06:45:00</td>\n",
       "      <td>-0.000109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>864</th>\n",
       "      <td>1.088496</td>\n",
       "      <td>1.088605</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-07-22 07:30:00</td>\n",
       "      <td>2024-07-22 12:30:00</td>\n",
       "      <td>-0.000109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>865</th>\n",
       "      <td>1.088874</td>\n",
       "      <td>1.088113</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-07-22 16:00:00</td>\n",
       "      <td>2024-07-22 17:00:00</td>\n",
       "      <td>0.000762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>866</th>\n",
       "      <td>1.088664</td>\n",
       "      <td>1.088773</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-07-22 19:15:00</td>\n",
       "      <td>2024-07-23 06:15:00</td>\n",
       "      <td>-0.000109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>867</th>\n",
       "      <td>1.084934</td>\n",
       "      <td>1.085043</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-07-25 10:30:00</td>\n",
       "      <td>2024-07-25 11:30:00</td>\n",
       "      <td>-0.000109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>868</th>\n",
       "      <td>1.084872</td>\n",
       "      <td>1.084980</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-07-25 19:15:00</td>\n",
       "      <td>2024-07-25 19:45:00</td>\n",
       "      <td>-0.000108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>869</th>\n",
       "      <td>1.082628</td>\n",
       "      <td>1.082520</td>\n",
       "      <td>short</td>\n",
       "      <td>2024-08-01 00:00:00</td>\n",
       "      <td>2024-08-01 00:15:00</td>\n",
       "      <td>-0.000108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>870</th>\n",
       "      <td>1.082908</td>\n",
       "      <td>1.082800</td>\n",
       "      <td>short</td>\n",
       "      <td>2024-08-01 03:00:00</td>\n",
       "      <td>2024-08-01 03:15:00</td>\n",
       "      <td>-0.000108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>871</th>\n",
       "      <td>1.082057</td>\n",
       "      <td>1.082815</td>\n",
       "      <td>short</td>\n",
       "      <td>2024-08-01 05:30:00</td>\n",
       "      <td>2024-08-01 06:15:00</td>\n",
       "      <td>0.000758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>872</th>\n",
       "      <td>1.082171</td>\n",
       "      <td>1.082062</td>\n",
       "      <td>short</td>\n",
       "      <td>2024-08-02 09:30:00</td>\n",
       "      <td>2024-08-02 11:00:00</td>\n",
       "      <td>-0.000108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>873</th>\n",
       "      <td>1.092156</td>\n",
       "      <td>1.091392</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-08-11 23:15:00</td>\n",
       "      <td>2024-08-12 01:30:00</td>\n",
       "      <td>0.000764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>874</th>\n",
       "      <td>1.092244</td>\n",
       "      <td>1.091480</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-08-12 04:00:00</td>\n",
       "      <td>2024-08-12 07:00:00</td>\n",
       "      <td>0.000764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>875</th>\n",
       "      <td>1.092271</td>\n",
       "      <td>1.092380</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-08-12 07:30:00</td>\n",
       "      <td>2024-08-12 07:45:00</td>\n",
       "      <td>-0.000109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>876</th>\n",
       "      <td>1.092228</td>\n",
       "      <td>1.092337</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-08-12 11:45:00</td>\n",
       "      <td>2024-08-12 12:30:00</td>\n",
       "      <td>-0.000109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>877</th>\n",
       "      <td>1.093205</td>\n",
       "      <td>1.092440</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-08-12 17:00:00</td>\n",
       "      <td>2024-08-12 18:00:00</td>\n",
       "      <td>0.000765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>878</th>\n",
       "      <td>1.092854</td>\n",
       "      <td>1.092090</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-08-13 10:15:00</td>\n",
       "      <td>2024-08-13 11:45:00</td>\n",
       "      <td>0.000764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>879</th>\n",
       "      <td>1.116526</td>\n",
       "      <td>1.116637</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-08-28 04:00:00</td>\n",
       "      <td>2024-08-28 04:30:00</td>\n",
       "      <td>-0.000112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>880</th>\n",
       "      <td>1.107973</td>\n",
       "      <td>1.107862</td>\n",
       "      <td>short</td>\n",
       "      <td>2024-09-04 20:00:00</td>\n",
       "      <td>2024-09-04 20:15:00</td>\n",
       "      <td>-0.000111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>881</th>\n",
       "      <td>1.107741</td>\n",
       "      <td>1.107630</td>\n",
       "      <td>short</td>\n",
       "      <td>2024-09-05 04:30:00</td>\n",
       "      <td>2024-09-05 05:00:00</td>\n",
       "      <td>-0.000111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>882</th>\n",
       "      <td>1.104875</td>\n",
       "      <td>1.104985</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-09-09 09:00:00</td>\n",
       "      <td>2024-09-09 10:15:00</td>\n",
       "      <td>-0.000110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>883</th>\n",
       "      <td>1.104117</td>\n",
       "      <td>1.104227</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-09-09 11:00:00</td>\n",
       "      <td>2024-09-09 11:15:00</td>\n",
       "      <td>-0.000110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>884</th>\n",
       "      <td>1.104172</td>\n",
       "      <td>1.104283</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-09-09 11:45:00</td>\n",
       "      <td>2024-09-09 14:00:00</td>\n",
       "      <td>-0.000110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>885</th>\n",
       "      <td>1.104545</td>\n",
       "      <td>1.104655</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-09-09 16:15:00</td>\n",
       "      <td>2024-09-09 18:00:00</td>\n",
       "      <td>-0.000110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>886</th>\n",
       "      <td>1.103805</td>\n",
       "      <td>1.103915</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-09-10 09:30:00</td>\n",
       "      <td>2024-09-10 10:15:00</td>\n",
       "      <td>-0.000110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>887</th>\n",
       "      <td>1.104590</td>\n",
       "      <td>1.104700</td>\n",
       "      <td>long</td>\n",
       "      <td>2024-09-11 07:15:00</td>\n",
       "      <td>2024-09-11 07:45:00</td>\n",
       "      <td>-0.000110</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     exit_price  entry_price   type          entry_time           exit_time  \\\n",
       "838    1.085511     1.085403  short 2024-05-27 13:30:00 2024-05-27 13:45:00   \n",
       "839    1.085966     1.086075   long 2024-05-27 16:45:00 2024-05-27 17:00:00   \n",
       "840    1.085884     1.085993   long 2024-05-28 19:30:00 2024-05-28 20:30:00   \n",
       "841    1.085659     1.085767   long 2024-05-28 21:15:00 2024-05-28 22:30:00   \n",
       "842    1.085449     1.085340  short 2024-06-03 02:30:00 2024-06-03 03:00:00   \n",
       "843    1.084693     1.085453  short 2024-06-03 03:15:00 2024-06-03 07:45:00   \n",
       "844    1.087226     1.086465   long 2024-06-04 12:00:00 2024-06-04 14:45:00   \n",
       "845    1.087368     1.086608   long 2024-06-05 11:45:00 2024-06-05 12:15:00   \n",
       "846    1.073248     1.073355   long 2024-06-24 22:45:00 2024-06-24 23:00:00   \n",
       "847    1.074349     1.073597   long 2024-06-30 22:45:00 2024-07-01 00:30:00   \n",
       "848    1.073895     1.074002   long 2024-07-01 20:45:00 2024-07-01 21:00:00   \n",
       "849    1.073798     1.073905   long 2024-07-01 22:00:00 2024-07-01 22:45:00   \n",
       "850    1.073383     1.073490   long 2024-07-02 14:45:00 2024-07-02 16:15:00   \n",
       "851    1.074139     1.073387   long 2024-07-02 17:00:00 2024-07-02 18:15:00   \n",
       "852    1.074589     1.073837   long 2024-07-03 05:30:00 2024-07-03 07:00:00   \n",
       "853    1.082788     1.082680  short 2024-07-08 03:00:00 2024-07-08 03:15:00   \n",
       "854    1.082593     1.082485  short 2024-07-09 02:30:00 2024-07-09 02:45:00   \n",
       "855    1.082078     1.081970  short 2024-07-09 08:30:00 2024-07-09 08:45:00   \n",
       "856    1.081873     1.081765  short 2024-07-09 13:00:00 2024-07-09 13:15:00   \n",
       "857    1.082068     1.081960  short 2024-07-10 04:00:00 2024-07-10 07:00:00   \n",
       "858    1.082041     1.081932  short 2024-07-10 09:45:00 2024-07-10 10:30:00   \n",
       "859    1.082473     1.082365  short 2024-07-10 15:00:00 2024-07-10 15:15:00   \n",
       "860    1.082496     1.082387  short 2024-07-10 16:00:00 2024-07-10 16:15:00   \n",
       "861    1.082168     1.082060  short 2024-07-10 18:30:00 2024-07-10 18:45:00   \n",
       "862    1.088484     1.088593   long 2024-07-22 06:00:00 2024-07-22 06:15:00   \n",
       "863    1.088456     1.088565   long 2024-07-22 06:30:00 2024-07-22 06:45:00   \n",
       "864    1.088496     1.088605   long 2024-07-22 07:30:00 2024-07-22 12:30:00   \n",
       "865    1.088874     1.088113   long 2024-07-22 16:00:00 2024-07-22 17:00:00   \n",
       "866    1.088664     1.088773   long 2024-07-22 19:15:00 2024-07-23 06:15:00   \n",
       "867    1.084934     1.085043   long 2024-07-25 10:30:00 2024-07-25 11:30:00   \n",
       "868    1.084872     1.084980   long 2024-07-25 19:15:00 2024-07-25 19:45:00   \n",
       "869    1.082628     1.082520  short 2024-08-01 00:00:00 2024-08-01 00:15:00   \n",
       "870    1.082908     1.082800  short 2024-08-01 03:00:00 2024-08-01 03:15:00   \n",
       "871    1.082057     1.082815  short 2024-08-01 05:30:00 2024-08-01 06:15:00   \n",
       "872    1.082171     1.082062  short 2024-08-02 09:30:00 2024-08-02 11:00:00   \n",
       "873    1.092156     1.091392   long 2024-08-11 23:15:00 2024-08-12 01:30:00   \n",
       "874    1.092244     1.091480   long 2024-08-12 04:00:00 2024-08-12 07:00:00   \n",
       "875    1.092271     1.092380   long 2024-08-12 07:30:00 2024-08-12 07:45:00   \n",
       "876    1.092228     1.092337   long 2024-08-12 11:45:00 2024-08-12 12:30:00   \n",
       "877    1.093205     1.092440   long 2024-08-12 17:00:00 2024-08-12 18:00:00   \n",
       "878    1.092854     1.092090   long 2024-08-13 10:15:00 2024-08-13 11:45:00   \n",
       "879    1.116526     1.116637   long 2024-08-28 04:00:00 2024-08-28 04:30:00   \n",
       "880    1.107973     1.107862  short 2024-09-04 20:00:00 2024-09-04 20:15:00   \n",
       "881    1.107741     1.107630  short 2024-09-05 04:30:00 2024-09-05 05:00:00   \n",
       "882    1.104875     1.104985   long 2024-09-09 09:00:00 2024-09-09 10:15:00   \n",
       "883    1.104117     1.104227   long 2024-09-09 11:00:00 2024-09-09 11:15:00   \n",
       "884    1.104172     1.104283   long 2024-09-09 11:45:00 2024-09-09 14:00:00   \n",
       "885    1.104545     1.104655   long 2024-09-09 16:15:00 2024-09-09 18:00:00   \n",
       "886    1.103805     1.103915   long 2024-09-10 09:30:00 2024-09-10 10:15:00   \n",
       "887    1.104590     1.104700   long 2024-09-11 07:15:00 2024-09-11 07:45:00   \n",
       "\n",
       "          pnl  \n",
       "838 -0.000109  \n",
       "839 -0.000109  \n",
       "840 -0.000109  \n",
       "841 -0.000109  \n",
       "842 -0.000109  \n",
       "843  0.000760  \n",
       "844  0.000761  \n",
       "845  0.000761  \n",
       "846 -0.000107  \n",
       "847  0.000752  \n",
       "848 -0.000107  \n",
       "849 -0.000107  \n",
       "850 -0.000107  \n",
       "851  0.000751  \n",
       "852  0.000752  \n",
       "853 -0.000108  \n",
       "854 -0.000108  \n",
       "855 -0.000108  \n",
       "856 -0.000108  \n",
       "857 -0.000108  \n",
       "858 -0.000108  \n",
       "859 -0.000108  \n",
       "860 -0.000108  \n",
       "861 -0.000108  \n",
       "862 -0.000109  \n",
       "863 -0.000109  \n",
       "864 -0.000109  \n",
       "865  0.000762  \n",
       "866 -0.000109  \n",
       "867 -0.000109  \n",
       "868 -0.000108  \n",
       "869 -0.000108  \n",
       "870 -0.000108  \n",
       "871  0.000758  \n",
       "872 -0.000108  \n",
       "873  0.000764  \n",
       "874  0.000764  \n",
       "875 -0.000109  \n",
       "876 -0.000109  \n",
       "877  0.000765  \n",
       "878  0.000764  \n",
       "879 -0.000112  \n",
       "880 -0.000111  \n",
       "881 -0.000111  \n",
       "882 -0.000110  \n",
       "883 -0.000110  \n",
       "884 -0.000110  \n",
       "885 -0.000110  \n",
       "886 -0.000110  \n",
       "887 -0.000110  "
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "strat_logs.tail(50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a54af502-c34f-422c-be61-ddbb27954e6f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ftiag\\AppData\\Local\\Temp\\ipykernel_13604\\2260884127.py:1: MatplotlibDeprecationWarning:\n",
      "\n",
      "The seaborn styles shipped by Matplotlib are deprecated since 3.6, as they no longer correspond to the styles shipped by seaborn. However, they will remain available as 'seaborn-v0_8-<style>'. Alternatively, directly use the seaborn API instead.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "plt.style.use('seaborn-darkgrid')\n",
    "\n",
    "# Convertir les index en format datetime\n",
    "data.index = pd.to_datetime(data.index)\n",
    "strat_logs['entry_time'] = pd.to_datetime(strat_logs['entry_time'])\n",
    "strat_logs['exit_time'] = pd.to_datetime(strat_logs['exit_time'])\n",
    "\n",
    "# Créer un index numérique pour les données\n",
    "data['index_num'] = range(len(data))\n",
    "index_mapping = pd.Series(data.index, index=data['index_num'])\n",
    "\n",
    "# Mapper les temps d'entrée et de sortie sur l'index numérique\n",
    "strat_logs['entry_index'] = strat_logs['entry_time'].map(data.reset_index().set_index('date')['index_num'])\n",
    "strat_logs['exit_index'] = strat_logs['exit_time'].map(data.reset_index().set_index('date')['index_num'])\n",
    "\n",
    "# Préparer le graphique\n",
    "plt.figure(figsize=(15, 7))\n",
    "\n",
    "# Tracer le prix ohlc4\n",
    "plt.plot(data['index_num'], data['ohlc4'], label='Prix OHLC4', color='#1f77b4', linewidth=1.5)\n",
    "\n",
    "# Ajouter les spreads des FVG\n",
    "plt.fill_between(data['index_num'], data['fvg_down'], data['fvg_up'], color='#ff7f0e', alpha=0.3, label='FVG')\n",
    "\n",
    "# Ajouter les spreads des buy order blocks\n",
    "plt.fill_between(data['index_num'], data['buy_breaker_block_low'], data['buy_breaker_block_high'], color='#2ca02c', alpha=0.4, label='Buy Order Block')\n",
    "\n",
    "# Ajouter les spreads des sell order blocks\n",
    "plt.fill_between(data['index_num'], data['sell_breaker_block_low'], data['sell_breaker_block_high'], color='#d62728', alpha=0.4, label='Sell Order Block')\n",
    "\n",
    "# Marquer les positions longues\n",
    "long_trades = strat_logs[strat_logs['type'] == 'long']\n",
    "plt.scatter(long_trades['entry_index'], long_trades['entry_price'], marker='^', color='#17becf', label='Entrée Longue', s=200)\n",
    "plt.scatter(long_trades['exit_index'], long_trades['exit_price'], marker='v', color='#e377c2', label='Sortie Longue', s=200)\n",
    "\n",
    "# Marquer les positions courtes\n",
    "short_trades = strat_logs[strat_logs['type'] == 'short']\n",
    "plt.scatter(short_trades['entry_index'], short_trades['entry_price'], marker='v', color='#bcbd22', label='Entrée Courte', s=200)\n",
    "plt.scatter(short_trades['exit_index'], short_trades['exit_price'], marker='^', color='#7f7f7f', label='Sortie Courte', s=200)\n",
    "\n",
    "# Ajuster l'axe des x pour afficher les dates sans gaps\n",
    "plt.xticks(data['index_num'][::int(len(data)/10)], data.index.strftime('%Y-%m-%d')[::int(len(data)/10)], rotation=45)\n",
    "\n",
    "# Ajouter des labels et une légende\n",
    "plt.xlabel('Date', fontsize=12)\n",
    "plt.ylabel('Prix', fontsize=12)\n",
    "plt.title('Positions de Trading avec FVG et Order Blocks', fontsize=14)\n",
    "plt.legend(loc='best', fontsize=10)\n",
    "plt.grid(True)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
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