NewDawnForex.ipynb

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    "# import matplotlib.pyplot as plt\n",
    "# import random, shutil, pickle, sys\n",
    "# import numpy as np\n",
    "# from collections import deque\n",
    "# from keras import Sequential\n",
    "# from keras.optimizers import RMSprop\n",
    "# from IPython.display import display\n",
    "# from PIL import Image\n",
    "import pandas as pd\n",
    "# from keras import Model\n",
    "# import keras, os, glob\n",
    "# import tensorflow as tf\n",
    "# from keras.layers import Layer, Dense, Flatten, RepeatVector,Dropout, LayerNormalization, MultiHeadAttention, GlobalAveragePooling1D\n",
    "# from keras.layers import Activation, Bidirectional ,Dropout\n",
    "# from keras import layers\n",
    "# # import cv2\n",
    "# # from sklearn.preprocessing import StandardScaler\n",
    "# import tensorflow as tf\n",
    "# # from sklearn.preprocessing import MinMaxScaler\n",
    "# import codecs\n",
    "# import csv\n",
    "# import secrets\n",
    "# import sqlite3\n",
    "# from IPython.display import display\n",
    "# from IPython.display import clear_output\n",
    "# import time\n",
    "# from tabulate import tabulate\n",
    "# import json\n",
    "# import datetime\n",
    "# from tensorflow.keras.optimizers import Adam\n",
    "# import math, datetime"
   ]
  },
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   "execution_count": 3,
   "id": "5a772a2d-abbd-4e82-885c-2069216765a0",
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    "m5short_step_4 = pd.read_csv(\"final_complete_m5short_timestep_4.csv\")\n",
    "m1short_step_4 = pd.read_csv(\"final_complete_m1short_timestep_4.csv\")\n",
    "m1long_step_4 = pd.read_csv(\"final_complete_m1long_timestep_4.csv\")\n",
    "m5long_step_4 = pd.read_csv(\"final_complete_m5long_timestep_4.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "78554d67-aeaa-45ec-bd73-ec881d7a2243",
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   "outputs": [],
   "source": [
    "position = None\n",
    "reward = 0\n",
    "profit = 0\n",
    "current_trade={}\n",
    "current_trade[\"entry_price\"] = 0\n",
    "a_profits = 0\n",
    "for k,v in m5long_step_4[:9000].iterrows():\n",
    "    ma10 = v[\"MA 10\"]\n",
    "    ma18 = v[\"MA 18\"]\n",
    "    ma30 = v[\"MA 30\"]\n",
    "    ma50 = v[\"MA 50\"]\n",
    "    \n",
    "    if ma10 < ma18 and ma10 < ma30:# and ma10 < ma50:\n",
    "        # print(f\"{k} reward 1 position sell\")\n",
    "        if position == \"buy\":\n",
    "            profit += current_trade[\"entry_price\"] - v[\"Bid\"]\n",
    "            position = None\n",
    "            print(\"Trade buy closed at\", v[\"Bid\"], \"profit\", profit , \" at \", k)\n",
    "        elif position == None:\n",
    "            current_trade[\"entry_price\"] = v[\"Bid\"]\n",
    "            position = \"sell\"\n",
    "        elif position == \"sell\":\n",
    "            print(\"accumulative_profits: \" , v[\"Bid\"] - current_trade[\"entry_price\"])\n",
    "            pass\n",
    "        \n",
    "    if ma10 > ma18 and ma10 > ma30:# and ma10 > ma50:\n",
    "        # print(f\"{k} reward 1 position buy\")\n",
    "        if position == \"sell\":\n",
    "            profit += v[\"Ask\"] - current_trade[\"entry_price\"]\n",
    "            position = None\n",
    "            print(\"Trade sell closed at\", v[\"Ask\"], \"profit\", profit, \" at \", k)\n",
    "        elif position == None:\n",
    "            current_trade[\"entry_price\"] = v[\"Ask\"]\n",
    "            position = \"buy\"\n",
    "            print(\"Trade position buy opened\")\n",
    "        elif position == \"buy\":\n",
    "            print(\"accumulative_profits: \" , abs(v[\"Bid\"] - current_trade[\"entry_price\"]))\n",
    "            pass\n",
    "print(\"Total_profits are \", profit)"
   ]
  },
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   "cell_type": "code",
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   "id": "f7fd625f-96b0-486c-8dbb-dd9491e66323",
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   "source": [
    "position = None\n",
    "reward = 0\n",
    "profit = 0\n",
    "current_trade={}\n",
    "current_trade[\"entry_price\"] = 0\n",
    "a_profits = 0\n",
    "for k , v in m5long_step_4[:9000].iterrows():\n",
    "    ma10 = v[\"MA 10\"]\n",
    "    ma18 = v[\"MA 18\"]\n",
    "    ma30 = v[\"MA 30\"]\n",
    "    ma50 = v[\"MA 50\"]\n",
    "    \n",
    "    if ma10 < ma18 and ma10 < ma30:# and ma10 < ma50:\n",
    "        # print(f\"{k} reward 1 position sell\")\n",
    "        if position == \"buy\":\n",
    "            profit += v[\"Bid\"] - current_trade[\"entry_price\"]\n",
    "            position = None\n",
    "            current_trade[\"entry_price\"] = 0\n",
    "            print(\"Trade buy closed at\", v[\"Bid\"], \"profit\", profit, \" at \", k)\n",
    "        elif position == None:\n",
    "            current_trade[\"entry_price\"] = v[\"Bid\"]\n",
    "            position = \"sell\"\n",
    "        elif position == \"sell\":\n",
    "            print(\"sell accumulative_profits: \" , current_trade[\"entry_price\"] - v[\"Ask\"])\n",
    "            pass\n",
    "        \n",
    "    if ma10 > ma18 and ma10 > ma30:# and ma10 > ma50:\n",
    "        # print(f\"{k} reward 1 position buy\")\n",
    "        if position == \"sell\":\n",
    "            profit += current_trade[\"entry_price\"]  - v[\"Ask\"]\n",
    "            position = None\n",
    "            \n",
    "            current_trade[\"entry_price\"] = 0\n",
    "\n",
    "            print(\"Trade sell closed at\", v[\"Ask\"], \"profit\", profit, \" at \", k)\n",
    "        elif position == None:\n",
    "            current_trade[\"entry_price\"] = v[\"Ask\"]\n",
    "            position = \"buy\"\n",
    "            print(\"Trade position buy opened\")\n",
    "        elif position == \"buy\":\n",
    "            print(\" buy accumulative_profits: \" ,  v[\"Bid\"] - current_trade[\"entry_price\"] )\n",
    "            pass\n",
    "print(\"Total_profits are \", profit)"
   ]
  },
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