474 lines
25 KiB
Plaintext
474 lines
25 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Strategy analysis example\n",
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"\n",
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"Debugging a strategy can be time-consuming. Freqtrade offers helper functions to visualize raw data.\n",
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"The following assumes you work with SampleStrategy, data for 5m timeframe from Binance and have downloaded them into the data directory in the default location."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Setup"
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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": 2,
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"metadata": {},
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"outputs": [
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{
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"ename": "OperationalException",
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"evalue": "Directory `/Users/surfer/Software/MMM/develop/freqtrade/freqtrade/templates/user_data` does not exist. Please use `freqtrade create-userdir` to create a user directory",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mOperationalException\u001b[0m Traceback (most recent call last)",
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"Input \u001b[0;32mIn [2]\u001b[0m, in \u001b[0;36m<cell line: 7>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mfreqtrade\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mconfiguration\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Configuration\n\u001b[1;32m 4\u001b[0m \u001b[38;5;66;03m# Customize these according to your needs.\u001b[39;00m\n\u001b[1;32m 5\u001b[0m \n\u001b[1;32m 6\u001b[0m \u001b[38;5;66;03m# Initialize empty configuration object\u001b[39;00m\n\u001b[0;32m----> 7\u001b[0m config \u001b[38;5;241m=\u001b[39m \u001b[43mConfiguration\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_files\u001b[49m\u001b[43m(\u001b[49m\u001b[43m[\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 8\u001b[0m \u001b[38;5;66;03m# Optionally, use existing configuration file\u001b[39;00m\n\u001b[1;32m 9\u001b[0m \u001b[38;5;66;03m# config = Configuration.from_files([\"config.json\"])\u001b[39;00m\n\u001b[1;32m 10\u001b[0m \n\u001b[1;32m 11\u001b[0m \u001b[38;5;66;03m# Define some constants\u001b[39;00m\n\u001b[1;32m 12\u001b[0m config[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtimeframe\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m1m\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
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"File \u001b[0;32m~/Software/MMM/develop/freqtrade/freqtrade/configuration/configuration.py:60\u001b[0m, in \u001b[0;36mConfiguration.from_files\u001b[0;34m(files)\u001b[0m\n\u001b[1;32m 58\u001b[0m \u001b[38;5;66;03m# Keep this method as staticmethod, so it can be used from interactive environments\u001b[39;00m\n\u001b[1;32m 59\u001b[0m c \u001b[38;5;241m=\u001b[39m Configuration({\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mconfig\u001b[39m\u001b[38;5;124m'\u001b[39m: files}, RunMode\u001b[38;5;241m.\u001b[39mOTHER)\n\u001b[0;32m---> 60\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mc\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_config\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
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"File \u001b[0;32m~/Software/MMM/develop/freqtrade/freqtrade/configuration/configuration.py:42\u001b[0m, in \u001b[0;36mConfiguration.get_config\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 37\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 38\u001b[0m \u001b[38;5;124;03mReturn the config. Use this method to get the bot config\u001b[39;00m\n\u001b[1;32m 39\u001b[0m \u001b[38;5;124;03m:return: Dict: Bot config\u001b[39;00m\n\u001b[1;32m 40\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 41\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconfig \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m---> 42\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconfig \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload_config\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 44\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconfig\n",
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"File \u001b[0;32m~/Software/MMM/develop/freqtrade/freqtrade/configuration/configuration.py:92\u001b[0m, in \u001b[0;36mConfiguration.load_config\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 88\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_process_common_options(config)\n\u001b[1;32m 90\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_process_trading_options(config)\n\u001b[0;32m---> 92\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_process_optimize_options\u001b[49m\u001b[43m(\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 94\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_process_plot_options(config)\n\u001b[1;32m 96\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_process_data_options(config)\n",
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"File \u001b[0;32m~/Software/MMM/develop/freqtrade/freqtrade/configuration/configuration.py:249\u001b[0m, in \u001b[0;36mConfiguration._process_optimize_options\u001b[0;34m(self, config)\u001b[0m\n\u001b[1;32m 242\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_args_to_config(config, argname\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfee\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m 243\u001b[0m logstring\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mParameter --fee detected, \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 244\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124msetting fee to: \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m ...\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 246\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_args_to_config(config, argname\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtimerange\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m 247\u001b[0m logstring\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mParameter --timerange detected: \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m ...\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m--> 249\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_process_datadir_options\u001b[49m\u001b[43m(\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 251\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_args_to_config(config, argname\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mstrategy_list\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m 252\u001b[0m logstring\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mUsing strategy list of \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m strategies\u001b[39m\u001b[38;5;124m'\u001b[39m, logfun\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mlen\u001b[39m)\n\u001b[1;32m 254\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_args_to_config(\n\u001b[1;32m 255\u001b[0m config,\n\u001b[1;32m 256\u001b[0m argname\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mrecursive_strategy_search\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m 257\u001b[0m logstring\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mRecursively searching for a strategy in the strategies folder.\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m 258\u001b[0m )\n",
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"File \u001b[0;32m~/Software/MMM/develop/freqtrade/freqtrade/configuration/configuration.py:180\u001b[0m, in \u001b[0;36mConfiguration._process_datadir_options\u001b[0;34m(self, config)\u001b[0m\n\u001b[1;32m 177\u001b[0m config\u001b[38;5;241m.\u001b[39mupdate({\u001b[38;5;124m'\u001b[39m\u001b[38;5;124muser_data_dir\u001b[39m\u001b[38;5;124m'\u001b[39m: \u001b[38;5;28mstr\u001b[39m(Path\u001b[38;5;241m.\u001b[39mcwd() \u001b[38;5;241m/\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124muser_data\u001b[39m\u001b[38;5;124m'\u001b[39m)})\n\u001b[1;32m 179\u001b[0m \u001b[38;5;66;03m# reset to user_data_dir so this contains the absolute path.\u001b[39;00m\n\u001b[0;32m--> 180\u001b[0m config[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124muser_data_dir\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[43mcreate_userdata_dir\u001b[49m\u001b[43m(\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43muser_data_dir\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcreate_dir\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m 181\u001b[0m logger\u001b[38;5;241m.\u001b[39minfo(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mUsing user-data directory: \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m ...\u001b[39m\u001b[38;5;124m'\u001b[39m, config[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124muser_data_dir\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[1;32m 183\u001b[0m config\u001b[38;5;241m.\u001b[39mupdate({\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdatadir\u001b[39m\u001b[38;5;124m'\u001b[39m: create_datadir(config, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39margs\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdatadir\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m))})\n",
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"File \u001b[0;32m~/Software/MMM/develop/freqtrade/freqtrade/configuration/directory_operations.py:61\u001b[0m, in \u001b[0;36mcreate_userdata_dir\u001b[0;34m(directory, create_dir)\u001b[0m\n\u001b[1;32m 59\u001b[0m logger\u001b[38;5;241m.\u001b[39minfo(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mCreated user-data directory: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfolder\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 60\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m---> 61\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m OperationalException(\n\u001b[1;32m 62\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDirectory `\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfolder\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m` does not exist. \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 63\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mPlease use `freqtrade create-userdir` to create a user directory\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 65\u001b[0m \u001b[38;5;66;03m# Create required subdirectories\u001b[39;00m\n\u001b[1;32m 66\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m f \u001b[38;5;129;01min\u001b[39;00m sub_dirs:\n",
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"\u001b[0;31mOperationalException\u001b[0m: Directory `/Users/surfer/Software/MMM/develop/freqtrade/freqtrade/templates/user_data` does not exist. Please use `freqtrade create-userdir` to create a user directory"
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]
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}
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],
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"source": [
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"from pathlib import Path\n",
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"from freqtrade.configuration import Configuration\n",
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"\n",
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"# Customize these according to your needs.\n",
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"\n",
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"# Initialize empty configuration object\n",
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"config = Configuration.from_files([])\n",
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"# Optionally, use existing configuration file\n",
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"# config = Configuration.from_files([\"config.json\"])\n",
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"\n",
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"# Define some constants\n",
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"config[\"timeframe\"] = \"1m\"\n",
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"# Name of the strategy class\n",
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"config[\"strategy\"] = \"MMMOracle\"\n",
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"# Location of the data\n",
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"data_location = Path(config['user_data_dir'], 'data', 'binance')\n",
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"# Pair to analyze - Only use one pair here\n",
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"pair = \"BTC/USDT\""
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# Load data using values set above\n",
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"from freqtrade.data.history import load_pair_history\n",
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"\n",
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"candles = load_pair_history(datadir=data_location,\n",
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" timeframe=config[\"timeframe\"],\n",
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" pair=pair,\n",
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" data_format = \"hdf5\",\n",
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" )\n",
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"\n",
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"# Confirm success\n",
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"print(\"Loaded \" + str(len(candles)) + f\" rows of data for {pair} from {data_location}\")\n",
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"candles.head()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Load and run strategy\n",
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"* Rerun each time the strategy file is changed"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# Load strategy using values set above\n",
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"from freqtrade.resolvers import StrategyResolver\n",
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"from freqtrade.data.dataprovider import DataProvider\n",
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"strategy = StrategyResolver.load_strategy(config)\n",
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"strategy.dp = DataProvider(config, None, None)\n",
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"\n",
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"# Generate buy/sell signals using strategy\n",
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"df = strategy.analyze_ticker(candles, {'pair': pair})\n",
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"df.tail()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Display the trade details\n",
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"\n",
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"* Note that using `data.head()` would also work, however most indicators have some \"startup\" data at the top of the dataframe.\n",
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"* Some possible problems\n",
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" * Columns with NaN values at the end of the dataframe\n",
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" * Columns used in `crossed*()` functions with completely different units\n",
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"* Comparison with full backtest\n",
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" * having 200 buy signals as output for one pair from `analyze_ticker()` does not necessarily mean that 200 trades will be made during backtesting.\n",
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" * Assuming you use only one condition such as, `df['rsi'] < 30` as buy condition, this will generate multiple \"buy\" signals for each pair in sequence (until rsi returns > 29). The bot will only buy on the first of these signals (and also only if a trade-slot (\"max_open_trades\") is still available), or on one of the middle signals, as soon as a \"slot\" becomes available. \n"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# Report results\n",
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"print(f\"Generated {df['enter_long'].sum()} entry signals\")\n",
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"data = df.set_index('date', drop=False)\n",
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"data.tail()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Load existing objects into a Jupyter notebook\n",
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"\n",
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"The following cells assume that you have already generated data using the cli. \n",
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"They will allow you to drill deeper into your results, and perform analysis which otherwise would make the output very difficult to digest due to information overload."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Load backtest results to pandas dataframe\n",
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"\n",
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"Analyze a trades dataframe (also used below for plotting)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 3,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"ename": "NameError",
|
|
"evalue": "name 'config' is not defined",
|
|
"output_type": "error",
|
|
"traceback": [
|
|
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
|
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
|
|
"Input \u001b[0;32mIn [3]\u001b[0m, in \u001b[0;36m<cell line: 4>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mfreqtrade\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdata\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mbtanalysis\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m load_backtest_data, load_backtest_stats\n\u001b[1;32m 3\u001b[0m \u001b[38;5;66;03m# if backtest_dir points to a directory, it'll automatically load the last backtest file.\u001b[39;00m\n\u001b[0;32m----> 4\u001b[0m backtest_dir \u001b[38;5;241m=\u001b[39m \u001b[43mconfig\u001b[49m[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124muser_data_dir\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m/\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mbacktest_results\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
|
|
"\u001b[0;31mNameError\u001b[0m: name 'config' is not defined"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"from freqtrade.data.btanalysis import load_backtest_data, load_backtest_stats\n",
|
|
"\n",
|
|
"# if backtest_dir points to a directory, it'll automatically load the last backtest file.\n",
|
|
"backtest_dir = config[\"user_data_dir\"] / \"backtest_results\"\n",
|
|
"# backtest_dir can also point to a specific file \n",
|
|
"# backtest_dir = config[\"user_data_dir\"] / \"backtest_results/backtest-result-2020-07-01_20-04-22.json\""
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# You can get the full backtest statistics by using the following command.\n",
|
|
"# This contains all information used to generate the backtest result.\n",
|
|
"stats = load_backtest_stats(backtest_dir)\n",
|
|
"\n",
|
|
"strategy = 'SampleStrategy'\n",
|
|
"# All statistics are available per strategy, so if `--strategy-list` was used during backtest, this will be reflected here as well.\n",
|
|
"# Example usages:\n",
|
|
"print(stats['strategy'][strategy]['results_per_pair'])\n",
|
|
"# Get pairlist used for this backtest\n",
|
|
"print(stats['strategy'][strategy]['pairlist'])\n",
|
|
"# Get market change (average change of all pairs from start to end of the backtest period)\n",
|
|
"print(stats['strategy'][strategy]['market_change'])\n",
|
|
"# Maximum drawdown ()\n",
|
|
"print(stats['strategy'][strategy]['max_drawdown'])\n",
|
|
"# Maximum drawdown start and end\n",
|
|
"print(stats['strategy'][strategy]['drawdown_start'])\n",
|
|
"print(stats['strategy'][strategy]['drawdown_end'])\n",
|
|
"\n",
|
|
"\n",
|
|
"# Get strategy comparison (only relevant if multiple strategies were compared)\n",
|
|
"print(stats['strategy_comparison'])\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Load backtested trades as dataframe\n",
|
|
"trades = load_backtest_data(backtest_dir)\n",
|
|
"\n",
|
|
"# Show value-counts per pair\n",
|
|
"trades.groupby(\"pair\")[\"exit_reason\"].value_counts()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Plotting daily profit / equity line"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Plotting equity line (starting with 0 on day 1 and adding daily profit for each backtested day)\n",
|
|
"\n",
|
|
"from freqtrade.configuration import Configuration\n",
|
|
"from freqtrade.data.btanalysis import load_backtest_data, load_backtest_stats\n",
|
|
"import plotly.express as px\n",
|
|
"import pandas as pd\n",
|
|
"\n",
|
|
"# strategy = 'SampleStrategy'\n",
|
|
"# config = Configuration.from_files([\"user_data/config.json\"])\n",
|
|
"# backtest_dir = config[\"user_data_dir\"] / \"backtest_results\"\n",
|
|
"\n",
|
|
"stats = load_backtest_stats(backtest_dir)\n",
|
|
"strategy_stats = stats['strategy'][strategy]\n",
|
|
"\n",
|
|
"dates = []\n",
|
|
"profits = []\n",
|
|
"for date_profit in strategy_stats['daily_profit']:\n",
|
|
" dates.append(date_profit[0])\n",
|
|
" profits.append(date_profit[1])\n",
|
|
"\n",
|
|
"equity = 0\n",
|
|
"equity_daily = []\n",
|
|
"for daily_profit in profits:\n",
|
|
" equity_daily.append(equity)\n",
|
|
" equity += float(daily_profit)\n",
|
|
"\n",
|
|
"\n",
|
|
"df = pd.DataFrame({'dates': dates,'equity_daily': equity_daily})\n",
|
|
"\n",
|
|
"fig = px.line(df, x=\"dates\", y=\"equity_daily\")\n",
|
|
"fig.show()\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"### Load live trading results into a pandas dataframe\n",
|
|
"\n",
|
|
"In case you did already some trading and want to analyze your performance"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"Series([], Name: exit_reason, dtype: int64)"
|
|
]
|
|
},
|
|
"execution_count": 4,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"from freqtrade.data.btanalysis import load_trades_from_db\n",
|
|
"\n",
|
|
"# Fetch trades from database\n",
|
|
"trades = load_trades_from_db(\"sqlite:///tradesv3.sqlite\")\n",
|
|
"\n",
|
|
"# Display results\n",
|
|
"trades.groupby(\"pair\")[\"exit_reason\"].value_counts()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Analyze the loaded trades for trade parallelism\n",
|
|
"This can be useful to find the best `max_open_trades` parameter, when used with backtesting in conjunction with `--disable-max-market-positions`.\n",
|
|
"\n",
|
|
"`analyze_trade_parallelism()` returns a timeseries dataframe with an \"open_trades\" column, specifying the number of open trades for each candle."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"from freqtrade.data.btanalysis import analyze_trade_parallelism\n",
|
|
"\n",
|
|
"# Analyze the above\n",
|
|
"parallel_trades = analyze_trade_parallelism(trades, '5m')\n",
|
|
"\n",
|
|
"parallel_trades.plot()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Plot results\n",
|
|
"\n",
|
|
"Freqtrade offers interactive plotting capabilities based on plotly."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"from freqtrade.plot.plotting import generate_candlestick_graph\n",
|
|
"# Limit graph period to keep plotly quick and reactive\n",
|
|
"\n",
|
|
"# Filter trades to one pair\n",
|
|
"trades_red = trades.loc[trades['pair'] == pair]\n",
|
|
"\n",
|
|
"data_red = data['2019-06-01':'2019-06-10']\n",
|
|
"# Generate candlestick graph\n",
|
|
"graph = generate_candlestick_graph(pair=pair,\n",
|
|
" data=data_red,\n",
|
|
" trades=trades_red,\n",
|
|
" indicators1=['sma20', 'ema50', 'ema55'],\n",
|
|
" indicators2=['rsi', 'macd', 'macdsignal', 'macdhist']\n",
|
|
" )\n",
|
|
"\n",
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Show graph inline\n",
|
|
"# graph.show()\n",
|
|
"\n",
|
|
"# Render graph in a seperate window\n",
|
|
"graph.show(renderer=\"browser\")\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"## Plot average profit per trade as distribution graph"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import plotly.figure_factory as ff\n",
|
|
"\n",
|
|
"hist_data = [trades.profit_ratio]\n",
|
|
"group_labels = ['profit_ratio'] # name of the dataset\n",
|
|
"\n",
|
|
"fig = ff.create_distplot(hist_data, group_labels, bin_size=0.01)\n",
|
|
"fig.show()\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"Feel free to submit an issue or Pull Request enhancing this document if you would like to share ideas on how to best analyze the data."
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"file_extension": ".py",
|
|
"kernelspec": {
|
|
"display_name": "Python 3 (ipykernel)",
|
|
"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": "3.9.7"
|
|
},
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"npconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"toc": {
|
|
"base_numbering": 1,
|
|
"nav_menu": {},
|
|
"number_sections": true,
|
|
"sideBar": true,
|
|
"skip_h1_title": false,
|
|
"title_cell": "Table of Contents",
|
|
"title_sidebar": "Contents",
|
|
"toc_cell": false,
|
|
"toc_position": {},
|
|
"toc_section_display": true,
|
|
"toc_window_display": false
|
|
},
|
|
"varInspector": {
|
|
"cols": {
|
|
"lenName": 16,
|
|
"lenType": 16,
|
|
"lenVar": 40
|
|
},
|
|
"kernels_config": {
|
|
"python": {
|
|
"delete_cmd_postfix": "",
|
|
"delete_cmd_prefix": "del ",
|
|
"library": "var_list.py",
|
|
"varRefreshCmd": "print(var_dic_list())"
|
|
},
|
|
"r": {
|
|
"delete_cmd_postfix": ") ",
|
|
"delete_cmd_prefix": "rm(",
|
|
"library": "var_list.r",
|
|
"varRefreshCmd": "cat(var_dic_list()) "
|
|
}
|
|
},
|
|
"types_to_exclude": [
|
|
"module",
|
|
"function",
|
|
"builtin_function_or_method",
|
|
"instance",
|
|
"_Feature"
|
|
],
|
|
"window_display": false
|
|
},
|
|
"version": 3
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 4
|
|
}
|