127 lines
4.9 KiB
Text
127 lines
4.9 KiB
Text
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "9ef899f2-2255-45b8-b8c5-5e6a182f8fdf",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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" Close-Open Close-Close1 Open-Close1 Open-Open1 \\\n",
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"Close-Open 1.000000 -0.000070 -0.705457 -0.992826 \n",
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"Close-Close1 -0.000070 1.000000 0.708802 0.011944 \n",
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"Open-Close1 -0.705457 0.708802 1.000000 0.708812 \n",
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"Open-Open1 -0.992826 0.011944 0.708812 1.000000 \n",
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"Open1-Close1 -0.002187 0.992821 0.705207 -0.000268 \n",
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"Close1-Close3 -0.018148 0.010820 0.020470 0.017589 \n",
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"Open-Close3 -0.506086 0.503291 0.713706 0.508041 \n",
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"Open-high1 -0.788011 0.419003 0.852838 0.794253 \n",
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"Open-low1 -0.793971 0.431464 0.865874 0.796894 \n",
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"Open-Close4 -0.456468 0.451330 0.641877 0.457735 \n",
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"Close1-Close3 -0.018148 0.010820 0.020470 0.017589 \n",
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"\n",
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" Open1-Close1 Close1-Close3 Open-Close3 Open-high1 \\\n",
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"Close-Open -0.002187 -0.018148 -0.506086 -0.788011 \n",
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"Close-Close1 0.992821 0.010820 0.503291 0.419003 \n",
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"Open-Close1 0.705207 0.020470 0.713706 0.852838 \n",
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"Open-Open1 -0.000268 0.017589 0.508041 0.794253 \n",
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"Open1-Close1 1.000000 0.011340 0.501142 0.410708 \n",
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"Close1-Close3 0.011340 1.000000 0.714908 0.020811 \n",
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"Open-Close3 0.501142 0.714908 1.000000 0.611026 \n",
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"Open-high1 0.410708 0.020811 0.611026 1.000000 \n",
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"Open-low1 0.426533 0.029066 0.625925 0.686956 \n",
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"Open-Close4 0.449878 0.640537 0.897661 0.548545 \n",
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"Close1-Close3 0.011340 1.000000 0.714908 0.020811 \n",
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"\n",
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" Open-low1 Open-Close4 Close1-Close3 \n",
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"Close-Open -0.793971 -0.456468 -0.018148 \n",
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"Close-Close1 0.431464 0.451330 0.010820 \n",
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"Open-Close1 0.865874 0.641877 0.020470 \n",
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"Open-Open1 0.796894 0.457735 0.017589 \n",
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"Open1-Close1 0.426533 0.449878 0.011340 \n",
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"Close1-Close3 0.029066 0.640537 1.000000 \n",
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"Open-Close3 0.625925 0.897661 0.714908 \n",
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"Open-high1 0.686956 0.548545 0.020811 \n",
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"Open-low1 1.000000 0.562178 0.029066 \n",
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"Open-Close4 0.562178 1.000000 0.640537 \n",
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"Close1-Close3 0.029066 0.640537 1.000000 \n"
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]
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}
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],
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"source": [
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"# Import Libraries\n",
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"import os\n",
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"import pandas as pd\n",
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"import numpy as np\n",
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"import MetaTrader5 as mt5\n",
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"\n",
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"\n",
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"# Load training dataset\n",
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"if not mt5.initialize():\n",
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" print(\"initialize() failed, error code =\",mt5.last_error())\n",
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" quit()\n",
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"\n",
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"path=os.path.join(mt5.terminal_info().data_path,r'MQL5\\Files')\n",
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"mt5.shutdown()\n",
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"filename = os.path.join(path,'pricecorr_delt.csv')\n",
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"data = pd.read_csv(filename,\n",
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" sep=',',\n",
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" skip_blank_lines=True,\n",
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" skipinitialspace=True,\n",
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" encoding='utf-8',\n",
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" float_precision='high',\n",
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" dtype=np.float64,\n",
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" low_memory=False)\n",
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"\n",
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"# Split training dataset to input data and target\n",
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"\n",
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"\n",
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"df = pd.DataFrame(data)\n",
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"correlation_matrix =df.drop(6).corr()\n",
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"print(correlation_matrix)\n",
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"filename = os.path.join(path,'pricecorr_delt_result.csv')\n",
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"correlation_matrix.to_csv(filename, encoding='utf-8')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "bccd7e31-e70d-4a0f-9b85-02962905f526",
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "e061b68a-150e-4536-b8fd-8bed1f7dc5ad",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.19"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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