├── .github └── workflows │ └── update_strat.yml ├── .gitignore ├── LICENSE ├── Makefile ├── README.md ├── docker-compose.yml ├── scripts ├── .DS_Store └── active-crontab.sh ├── templates ├── config.json.template ├── config.private.json.template └── update-crypto-bot.sh.template └── user_data ├── config.backtesting.json ├── config.json ├── hyperopts └── sample_hyperopt_loss.py ├── logs └── .gitkeep ├── notebooks └── strategy_analysis_example.ipynb └── strategies ├── NostalgiaForInfinityX.py ├── NostalgiaForInfinityX ├── blacklist-binance.json └── pairlist-volume-binance-usdt.json └── SampleStrategy.py /.github/workflows/update_strat.yml: -------------------------------------------------------------------------------- 1 | name: Get latest release version 2 | on: 3 | schedule: 4 | - cron: '2-59/5 * * * *' 5 | jobs: 6 | get-version: 7 | runs-on: ubuntu-latest 8 | steps: 9 | - uses: actions/checkout@v3 10 | - name: Fetch release version 11 | run: | 12 | curl -O https://raw.githubusercontent.com/iterativv/NostalgiaForInfinity/main/NostalgiaForInfinityX.py && \ 13 | mv NostalgiaForInfinityX.py user_data/strategies 14 | curl -O https://raw.githubusercontent.com/iterativv/NostalgiaForInfinity/main/configs/blacklist-binance.json && \ 15 | mv blacklist-binance.json user_data/strategies/NostalgiaForInfinityX 16 | curl -O https://raw.githubusercontent.com/iterativv/NostalgiaForInfinity/main/configs/pairlist-volume-binance-usdt.json && \ 17 | mv pairlist-volume-binance-usdt.json user_data/strategies/NostalgiaForInfinityX 18 | - name: Check for modified files 19 | id: git-check 20 | run: echo "modified=$([ -z "`git status --porcelain`" ] && echo "false" || echo "true")" >> $GITHUB_OUTPUT 21 | - name: Commit latest release version 22 | if: steps.git-check.outputs.modified == 'true' 23 | run: | 24 | git config user.name 'github-actions' 25 | git config user.email 'github-actions@github.com' 26 | git add . 27 | git commit -am "Update NostalgiaForInfinityX Strategy" 28 | git push 29 | - name: Notify Telegram 30 | uses: appleboy/telegram-action@master 31 | if: steps.git-check.outputs.modified == 'true' 32 | with: 33 | to: ${{ secrets.TELEGRAM_TO }} 34 | token: ${{ secrets.TELEGRAM_TOKEN }} 35 | args: Config Files updated. 36 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | .DS_Store 2 | user_data/data* 3 | user_data/plot* 4 | user_data/*.sqlite 5 | user_data/hyperopt.lock 6 | user_data/hyperopt_results 7 | user_data/backtest_results 8 | user_data/config.private.json 9 | user_data/logs/freqtrade.log 10 | nfi-profit_maximizer-freqtrade-binance-USDT-(backtest).json 11 | tradesv3.sqlite-shm 12 | tradesv3.sqlite-wal -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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Interpretation of Sections 15 and 16. 613 | 614 | If the disclaimer of warranty and limitation of liability provided 615 | above cannot be given local legal effect according to their terms, 616 | reviewing courts shall apply local law that most closely approximates 617 | an absolute waiver of all civil liability in connection with the 618 | Program, unless a warranty or assumption of liability accompanies a 619 | copy of the Program in return for a fee. 620 | 621 | END OF TERMS AND CONDITIONS 622 | 623 | How to Apply These Terms to Your New Programs 624 | 625 | If you develop a new program, and you want it to be of the greatest 626 | possible use to the public, the best way to achieve this is to make it 627 | free software which everyone can redistribute and change under these terms. 628 | 629 | To do so, attach the following notices to the program. It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /Makefile: -------------------------------------------------------------------------------- 1 | FREQTRADE_RUN := docker-compose run --rm freqtrade 2 | 3 | CONFIG := --config user_data/config.json 4 | CONFIG_PRIVATE := --config user_data/config.private.json 5 | CONFIG_BACKTESTING := --config user_data/config.backtesting.json 6 | 7 | TIME_DATA = --timerange $(or $(TIMERANGE),20220101-20220201) --timeframe $(or $(TIMEFRAME),5m) 8 | TEST_ARGS := --strategy $(or $(STRATEGY),SampleStrategy) $(TIME_DATA) 9 | 10 | STRATEGIES := $(shell ls user_data/strategies | grep py | sed "s/.py//g" | tr "\n" " ") 11 | 12 | list-exchanges: 13 | $(FREQTRADE_RUN) list-exchanges 14 | 15 | list-strats: 16 | $(FREQTRADE_RUN) list-strategies 17 | 18 | list-pairs: 19 | $(FREQTRADE_RUN) list-pairs --exchange $(or $(EXCHANGE),binance) --quote $(or $(QUOTE),USDT) 20 | 21 | list-timeframes: 22 | $(FREQTRADE_RUN) list-timeframes --exchange $(or $(EXCHANGE),binance) 23 | 24 | list-data: 25 | $(FREQTRADE_RUN) list-data --exchange $(or $(EXCHANGE),binance) 26 | 27 | test-pairlist:* 28 | $(FREQTRADE_RUN) test-pairlist $(CONFIG_BACKTESTING) --exchange $(or $(EXCHANGE),binance) --quote $(or $(QUOTE),USDT) 29 | 30 | download-data: 31 | $(FREQTRADE_RUN) download-data $(CONFIG_BACKTESTING) --exchange $(or $(EXCHANGE),binance) $(TIME_DATA) 32 | 33 | backtesting: 34 | $(FREQTRADE_RUN) backtesting $(CONFIG) $(CONFIG_PRIVATE) $(CONFIG_BACKTESTING) $(TEST_ARGS) 35 | 36 | # Image Required: develop_plot or stable_plot 37 | plot-dataframe: 38 | $(FREQTRADE_RUN) plot-dataframe $(CONFIG) $(CONFIG_PRIVATE) $(CONFIG_BACKTESTING) $(TEST_ARGS) 39 | plot-profit: 40 | $(FREQTRADE_RUN) plot-profit $(CONFIG) $(CONFIG_PRIVATE) $(CONFIG_BACKTESTING) $(TEST_ARGS) 41 | 42 | backtesting-all: 43 | $(FREQTRADE_RUN) backtesting $(CONFIG) $(CONFIG_PRIVATE) $(CONFIG_BACKTESTING) --strategy-list $(STRATEGIES) $(TIME_DATA) 44 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Crypto Bot 2 | 3 | [Freqtrade](https://www.freqtrade.io/en/stable/) Crypto Bot with [NostalgiaForInfinity](https://github.com/iterativv/NostalgiaForInfinity) Strategy.
4 | *The strategy is constantly updated from a Github Action.* 5 | 6 | ## Getting Started 7 | 8 | If not already done, install [Docker](https://docs.docker.com/engine/install/) and [Docker Compose](https://docs.docker.com/compose/install/other/) 9 | 10 | **Clone repository** 11 | ```bash 12 | git clone https://github.com/kerycdiaz/crypto-bot.git && cd crypto-bot 13 | ``` 14 | **Generate the private configuration file** 15 | ```bash 16 | cp templates/config.private.json.template user_data/config.private.json 17 | ``` 18 | **Start Crypto Bot.** *(By default the mode is enabled **Dry-Run**)* 19 | ```bash 20 | docker-compose up -d 21 | ``` 22 | To access FreqUI go to `http://localhost:8080/` and register a new bot with the username and password that indicates the `config.private.json` ***(You can change it at any time)***. In the same file you can activate telegram notifications, configure the exchange credentials and disable dry-run mode. 23 | 24 | 25 | ## Automatically Update Crypto Bot 26 | 27 | ```bash 28 | cp templates/update-crypto-bot.sh.template scripts/update-crypto-bot.sh 29 | cd ${HOME}/crypto-bot/scripts 30 | # In update-crypto-bot.sh, add TG_TOKEN, TG_CHAT_ID and confirm the CRYPTO_BOT_PATH (Path where you cloned your project) 31 | chmod -x active-crontab.sh && ./active-crontab.sh 32 | ``` 33 | 34 | 35 | ## Backtesting 36 | 37 | If not already done, install Make: `sudo apt install make`
38 | *Note: All parameters are optional, I could see their default value in the [Makefile](https://github.com/kerycdiaz/crypto-bot/blob/main/Makefile)* 39 | 40 | **Download the pairs you need to perform backtesting** 41 | ```bash 42 | make download-data EXCHANGE=binance TIMERANGE=20220101-20220201 TIMEFRAME='5m' 43 | ``` 44 | 45 | **Know the downloaded pairs and their temporality** 46 | ```bash 47 | make list-data EXCHANGE=binance 48 | ``` 49 | 50 | **Running backtesting for a defined strategy** 51 | ```bash 52 | make backtesting EXCHANGE=binance STRATEGY=SampleStrategy TIMERANGE=20220101-20220201 TIMEFRAME='5m' 53 | ``` 54 | 55 | ***If you want to backtest the `NostalgiaForInfinityX` strategy you must download the data for `'5m 15m 1h 1d'`*** 56 | ____ 57 | ## Disclaimer 58 | 59 | This is a personal experimentation software. Do not risk money which 60 | you are afraid to lose. USE THE SOFTWARE AT YOUR OWN RISK. THE AUTHORS 61 | AND ALL AFFILIATES ASSUME NO RESPONSIBILITY FOR YOUR TRADING RESULTS. 62 | ____ 63 | 64 | ## Credits 65 | 66 | Created by [Keryc Díaz](https://www.linkedin.com/in/kerycdiaz/), NostalgiaForInfinity maintained by [Iterativ](https://github.com/iterativv). 67 | -------------------------------------------------------------------------------- /docker-compose.yml: -------------------------------------------------------------------------------- 1 | --- 2 | version: '3' 3 | services: 4 | freqtrade: 5 | image: freqtradeorg/freqtrade:stable 6 | # image: freqtradeorg/freqtrade:develop 7 | # Use plotting image 8 | # image: freqtradeorg/freqtrade:develop_plot 9 | # Build step - only needed when additional dependencies are needed 10 | # build: 11 | # context: . 12 | # dockerfile: "./docker/Dockerfile.custom" 13 | restart: unless-stopped 14 | container_name: freqtrade 15 | volumes: 16 | - "./user_data:/freqtrade/user_data" 17 | # Expose api on port 8080 (localhost only) 18 | # Please read the https://www.freqtrade.io/en/stable/rest-api/ documentation 19 | # before enabling this. 20 | ports: 21 | - "127.0.0.1:8080:8080" 22 | 23 | # Default command used when running `docker compose up` 24 | # command: > 25 | # trade 26 | # --logfile /freqtrade/user_data/logs/freqtrade.log 27 | # --db-url sqlite:////freqtrade/user_data/tradesv3.sqlite 28 | # --config /freqtrade/user_data/config.json 29 | # --config /freqtrade/user_data/config.private.json 30 | # --strategy SampleStrategy 31 | 32 | # Command to run NostalgiaForInfinityX strategy 33 | command: > 34 | trade 35 | --logfile /freqtrade/user_data/logs/freqtrade.log 36 | --db-url sqlite:////freqtrade/user_data/tradesv3.sqlite 37 | --config /freqtrade/user_data/config.json 38 | --config /freqtrade/user_data/config.private.json 39 | --config /freqtrade/user_data/strategies/NostalgiaForInfinityX/pairlist-volume-binance-usdt.json 40 | --config /freqtrade/user_data/strategies/NostalgiaForInfinityX/blacklist-binance.json 41 | --strategy NostalgiaForInfinityX 42 | -------------------------------------------------------------------------------- /scripts/.DS_Store: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/keryc/crypto-bot/55159a8aa549e06e63b313552785ccd07fc36a77/scripts/.DS_Store -------------------------------------------------------------------------------- /scripts/active-crontab.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | LINE="2-59/5 * * * * /bin/bash -c ${PWD}/update-crypto-bot.sh" && 4 | (crontab -l; echo "$LINE" ) | crontab - 5 | -------------------------------------------------------------------------------- /templates/config.json.template: -------------------------------------------------------------------------------- 1 | { 2 | // Configuration created when running the command: 3 | // freqtrade new-config --config user_data/config.json 4 | "max_open_trades": 3, 5 | "stake_currency": "USDT", 6 | "stake_amount": "unlimited", 7 | "tradable_balance_ratio": 0.99, 8 | "fiat_display_currency": "USD", 9 | "dry_run": true, 10 | "dry_run_wallet": 1000, 11 | "cancel_open_orders_on_exit": false, 12 | "trading_mode": "spot", 13 | "margin_mode": "", 14 | "unfilledtimeout": { 15 | "entry": 10, 16 | "exit": 10, 17 | "exit_timeout_count": 0, 18 | "unit": "minutes" 19 | }, 20 | "entry_pricing": { 21 | "price_side": "same", 22 | "use_order_book": true, 23 | "order_book_top": 1, 24 | "price_last_balance": 0.0, 25 | "check_depth_of_market": { 26 | "enabled": false, 27 | "bids_to_ask_delta": 1 28 | } 29 | }, 30 | "exit_pricing":{ 31 | "price_side": "same", 32 | "use_order_book": true, 33 | "order_book_top": 1 34 | }, 35 | "pairlists": [ 36 | { 37 | "method": "VolumePairList", 38 | "number_assets": 20, 39 | "sort_key": "quoteVolume", 40 | "min_value": 0, 41 | "refresh_period": 1800 42 | } 43 | ], 44 | "edge": { 45 | "enabled": false, 46 | "process_throttle_secs": 3600, 47 | "calculate_since_number_of_days": 7, 48 | "allowed_risk": 0.01, 49 | "stoploss_range_min": -0.01, 50 | "stoploss_range_max": -0.1, 51 | "stoploss_range_step": -0.01, 52 | "minimum_winrate": 0.60, 53 | "minimum_expectancy": 0.20, 54 | "min_trade_number": 10, 55 | "max_trade_duration_minute": 1440, 56 | "remove_pumps": false 57 | } 58 | } -------------------------------------------------------------------------------- /templates/config.private.json.template: -------------------------------------------------------------------------------- 1 | { 2 | "dry_run": true, 3 | "stake_currency": "USDT", 4 | "fiat_display_currency": "USD", 5 | "cancel_open_orders_on_exit": false, 6 | "exchange": { 7 | "name": "binance", 8 | "key": "", 9 | "secret": "", 10 | "ccxt_config": {}, 11 | "ccxt_async_config": {}, 12 | "pair_whitelist": [ 13 | ], 14 | "pair_blacklist": [ 15 | "BNB/.*" 16 | ] 17 | }, 18 | "telegram": { 19 | "enabled": true, 20 | "token": "", 21 | "chat_id": "" 22 | }, 23 | "api_server": { 24 | "enabled": true, 25 | "listen_ip_address": "0.0.0.0", 26 | "listen_port": 8080, 27 | "verbosity": "error", 28 | "enable_openapi": false, 29 | "jwt_secret_key": "somethingrandom", 30 | "ws_token": "sercet_Ws_t0ken", 31 | "CORS_origins": [], 32 | "username": "Freqtrader", 33 | "password": "SuperSecret1!" 34 | }, 35 | "bot_name": "freqtrade", 36 | "initial_state": "running", 37 | "force_entry_enable": false, 38 | "internals": { 39 | "process_throttle_secs": 5 40 | } 41 | } -------------------------------------------------------------------------------- /templates/update-crypto-bot.sh.template: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | TG_TOKEN="" 4 | TG_CHAT_ID="" 5 | 6 | CRYPTO_BOT_PATH="${HOME}/crypto-bot" && cd $CRYPTO_BOT_PATH 7 | 8 | GITRESPONSE=`git pull` && UPDATED='Already up to date.' 9 | 10 | if [[ $GITRESPONSE != $UPDATED ]]; then 11 | GITCOMMITTER=`git show -s --format='%cn'` 12 | GITVERSION=`git show -s --format='%h'` 13 | GITCOMMENT=`git show -s --format='%s'` 14 | 15 | curl -s --data "text=🆕 Update Crypto Bot by ${GITCOMMITTER}!%0ACommit: $GITVERSION%0AComment: ${GITCOMMENT}%0A⏳ Please wait for reload..." \ 16 | --data "parse_mode=HTML" \ 17 | --data "chat_id=$TG_CHAT_ID" \ 18 | "https://api.telegram.org/bot${TG_TOKEN}/sendMessage" 19 | 20 | /usr/local/bin/docker-compose restart > /dev/null && 21 | 22 | curl -s --data "text=🆗 CB reload has been completed!" \ 23 | --data "parse_mode=HTML" \ 24 | --data "chat_id=$TG_CHAT_ID" \ 25 | "https://api.telegram.org/bot${TG_TOKEN}/sendMessage" 26 | fi 27 | -------------------------------------------------------------------------------- /user_data/config.backtesting.json: -------------------------------------------------------------------------------- 1 | { 2 | "exchange": { 3 | "pair_whitelist": [ 4 | "BTC/USDT", 5 | "ETH/USDT", 6 | "LUNA/USDT", 7 | "FTM/USDT", 8 | "SOL/USDT", 9 | "ADA/USDT", 10 | "XRP/USDT", 11 | "DOT/USDT", 12 | "SHIB/USDT", 13 | "MATIC/USDT", 14 | "ATOM/USDT", 15 | "NEAR/USDT", 16 | "SAND/USDT", 17 | "LINK/USDT", 18 | "DOGE/USDT", 19 | "GALA/USDT", 20 | "ROSE/USDT", 21 | "AVAX/USDT" 22 | ], 23 | "pair_blacklist": [ 24 | "BNB/.*", 25 | ] 26 | }, 27 | "pairlists": [ 28 | { 29 | "method": "StaticPairList" 30 | } 31 | ], 32 | } -------------------------------------------------------------------------------- /user_data/config.json: -------------------------------------------------------------------------------- 1 | { 2 | // WARNING: This is an example configuration to use with NostalgiaForInfinityX. 3 | // Please use at own risk 4 | // For full documentation on Freqtrade configration files please visit https://www.freqtrade.io/en/stable/configuration/ 5 | "dry_run": true, 6 | "max_open_trades": 6, 7 | "stake_currency": "USDT", 8 | "stake_amount": "unlimited", 9 | "tradable_balance_ratio": 0.99, 10 | "fiat_display_currency": "USD", 11 | "force_entry_enable": true, 12 | "unfilledtimeout": { 13 | "entry": 15, 14 | "exit": 15, 15 | "exit_timeout_count": 0, 16 | "unit": "minutes" 17 | }, 18 | "order_types": { 19 | "entry": "limit", 20 | "exit": "limit", 21 | "emergency_exit": "limit", 22 | "force_entry": "limit", 23 | "force_exit": "limit", 24 | "stoploss": "limit", 25 | "stoploss_on_exchange": false, 26 | "stoploss_on_exchange_interval": 60 27 | }, 28 | "entry_pricing": { 29 | "price_side": "other", 30 | "use_order_book": false, 31 | "order_book_top": 1, 32 | "price_last_balance": 0.0, 33 | "check_depth_of_market": {"enabled": false, "bids_to_ask_delta": 1}, 34 | }, 35 | "exit_pricing": { 36 | "price_side": "other", 37 | "use_order_book": false, 38 | "order_book_top": 1, 39 | "price_last_balance": 0.0, 40 | }, 41 | } 42 | -------------------------------------------------------------------------------- /user_data/hyperopts/sample_hyperopt_loss.py: -------------------------------------------------------------------------------- 1 | from datetime import datetime 2 | from math import exp 3 | from typing import Dict 4 | 5 | from pandas import DataFrame 6 | 7 | from freqtrade.constants import Config 8 | from freqtrade.optimize.hyperopt import IHyperOptLoss 9 | 10 | 11 | # Define some constants: 12 | 13 | # set TARGET_TRADES to suit your number concurrent trades so its realistic 14 | # to the number of days 15 | TARGET_TRADES = 600 16 | # This is assumed to be expected avg profit * expected trade count. 17 | # For example, for 0.35% avg per trade (or 0.0035 as ratio) and 1100 trades, 18 | # self.expected_max_profit = 3.85 19 | # Check that the reported Σ% values do not exceed this! 20 | # Note, this is ratio. 3.85 stated above means 385Σ%. 21 | EXPECTED_MAX_PROFIT = 3.0 22 | 23 | # max average trade duration in minutes 24 | # if eval ends with higher value, we consider it a failed eval 25 | MAX_ACCEPTED_TRADE_DURATION = 300 26 | 27 | 28 | class SampleHyperOptLoss(IHyperOptLoss): 29 | """ 30 | Defines the default loss function for hyperopt 31 | This is intended to give you some inspiration for your own loss function. 32 | 33 | The Function needs to return a number (float) - which becomes smaller for better backtest 34 | results. 35 | """ 36 | 37 | @staticmethod 38 | def hyperopt_loss_function(results: DataFrame, trade_count: int, 39 | min_date: datetime, max_date: datetime, 40 | config: Config, processed: Dict[str, DataFrame], 41 | *args, **kwargs) -> float: 42 | """ 43 | Objective function, returns smaller number for better results 44 | """ 45 | total_profit = results['profit_ratio'].sum() 46 | trade_duration = results['trade_duration'].mean() 47 | 48 | trade_loss = 1 - 0.25 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.8) 49 | profit_loss = max(0, 1 - total_profit / EXPECTED_MAX_PROFIT) 50 | duration_loss = 0.4 * min(trade_duration / MAX_ACCEPTED_TRADE_DURATION, 1) 51 | result = trade_loss + profit_loss + duration_loss 52 | return result 53 | -------------------------------------------------------------------------------- /user_data/logs/.gitkeep: -------------------------------------------------------------------------------- 1 | .gitkeep -------------------------------------------------------------------------------- /user_data/notebooks/strategy_analysis_example.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": {}, 6 | "source": [ 7 | "# Strategy analysis example\n", 8 | "\n", 9 | "Debugging a strategy can be time-consuming. Freqtrade offers helper functions to visualize raw data.\n", 10 | "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." 11 | ] 12 | }, 13 | { 14 | "cell_type": "markdown", 15 | "metadata": {}, 16 | "source": [ 17 | "## Setup" 18 | ] 19 | }, 20 | { 21 | "cell_type": "code", 22 | "execution_count": null, 23 | "metadata": {}, 24 | "outputs": [], 25 | "source": [ 26 | "from pathlib import Path\n", 27 | "from freqtrade.configuration import Configuration\n", 28 | "\n", 29 | "# Customize these according to your needs.\n", 30 | "\n", 31 | "# Initialize empty configuration object\n", 32 | "config = Configuration.from_files([])\n", 33 | "# Optionally (recommended), use existing configuration file\n", 34 | "# config = Configuration.from_files([\"config.json\"])\n", 35 | "\n", 36 | "# Define some constants\n", 37 | "config[\"timeframe\"] = \"5m\"\n", 38 | "# Name of the strategy class\n", 39 | "config[\"strategy\"] = \"SampleStrategy\"\n", 40 | "# Location of the data\n", 41 | "data_location = config['datadir']\n", 42 | "# Pair to analyze - Only use one pair here\n", 43 | "pair = \"BTC/USDT\"" 44 | ] 45 | }, 46 | { 47 | "cell_type": "code", 48 | "execution_count": null, 49 | "metadata": {}, 50 | "outputs": [], 51 | "source": [ 52 | "# Load data using values set above\n", 53 | "from freqtrade.data.history import load_pair_history\n", 54 | "from freqtrade.enums import CandleType\n", 55 | "\n", 56 | "candles = load_pair_history(datadir=data_location,\n", 57 | " timeframe=config[\"timeframe\"],\n", 58 | " pair=pair,\n", 59 | " data_format = \"hdf5\",\n", 60 | " candle_type=CandleType.SPOT,\n", 61 | " )\n", 62 | "\n", 63 | "# Confirm success\n", 64 | "print(\"Loaded \" + str(len(candles)) + f\" rows of data for {pair} from {data_location}\")\n", 65 | "candles.head()" 66 | ] 67 | }, 68 | { 69 | "cell_type": "markdown", 70 | "metadata": {}, 71 | "source": [ 72 | "## Load and run strategy\n", 73 | "* Rerun each time the strategy file is changed" 74 | ] 75 | }, 76 | { 77 | "cell_type": "code", 78 | "execution_count": null, 79 | "metadata": {}, 80 | "outputs": [], 81 | "source": [ 82 | "# Load strategy using values set above\n", 83 | "from freqtrade.resolvers import StrategyResolver\n", 84 | "from freqtrade.data.dataprovider import DataProvider\n", 85 | "strategy = StrategyResolver.load_strategy(config)\n", 86 | "strategy.dp = DataProvider(config, None, None)\n", 87 | "\n", 88 | "# Generate buy/sell signals using strategy\n", 89 | "df = strategy.analyze_ticker(candles, {'pair': pair})\n", 90 | "df.tail()" 91 | ] 92 | }, 93 | { 94 | "cell_type": "markdown", 95 | "metadata": {}, 96 | "source": [ 97 | "### Display the trade details\n", 98 | "\n", 99 | "* Note that using `data.head()` would also work, however most indicators have some \"startup\" data at the top of the dataframe.\n", 100 | "* Some possible problems\n", 101 | " * Columns with NaN values at the end of the dataframe\n", 102 | " * Columns used in `crossed*()` functions with completely different units\n", 103 | "* Comparison with full backtest\n", 104 | " * 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", 105 | " * 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" 106 | ] 107 | }, 108 | { 109 | "cell_type": "code", 110 | "execution_count": null, 111 | "metadata": {}, 112 | "outputs": [], 113 | "source": [ 114 | "# Report results\n", 115 | "print(f\"Generated {df['enter_long'].sum()} entry signals\")\n", 116 | "data = df.set_index('date', drop=False)\n", 117 | "data.tail()" 118 | ] 119 | }, 120 | { 121 | "cell_type": "markdown", 122 | "metadata": {}, 123 | "source": [ 124 | "## Load existing objects into a Jupyter notebook\n", 125 | "\n", 126 | "The following cells assume that you have already generated data using the cli. \n", 127 | "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." 128 | ] 129 | }, 130 | { 131 | "cell_type": "markdown", 132 | "metadata": {}, 133 | "source": [ 134 | "### Load backtest results to pandas dataframe\n", 135 | "\n", 136 | "Analyze a trades dataframe (also used below for plotting)" 137 | ] 138 | }, 139 | { 140 | "cell_type": "code", 141 | "execution_count": null, 142 | "metadata": {}, 143 | "outputs": [], 144 | "source": [ 145 | "from freqtrade.data.btanalysis import load_backtest_data, load_backtest_stats\n", 146 | "\n", 147 | "# if backtest_dir points to a directory, it'll automatically load the last backtest file.\n", 148 | "backtest_dir = config[\"user_data_dir\"] / \"backtest_results\"\n", 149 | "# backtest_dir can also point to a specific file \n", 150 | "# backtest_dir = config[\"user_data_dir\"] / \"backtest_results/backtest-result-2020-07-01_20-04-22.json\"" 151 | ] 152 | }, 153 | { 154 | "cell_type": "code", 155 | "execution_count": null, 156 | "metadata": {}, 157 | "outputs": [], 158 | "source": [ 159 | "# You can get the full backtest statistics by using the following command.\n", 160 | "# This contains all information used to generate the backtest result.\n", 161 | "stats = load_backtest_stats(backtest_dir)\n", 162 | "\n", 163 | "strategy = 'SampleStrategy'\n", 164 | "# All statistics are available per strategy, so if `--strategy-list` was used during backtest, this will be reflected here as well.\n", 165 | "# Example usages:\n", 166 | "print(stats['strategy'][strategy]['results_per_pair'])\n", 167 | "# Get pairlist used for this backtest\n", 168 | "print(stats['strategy'][strategy]['pairlist'])\n", 169 | "# Get market change (average change of all pairs from start to end of the backtest period)\n", 170 | "print(stats['strategy'][strategy]['market_change'])\n", 171 | "# Maximum drawdown ()\n", 172 | "print(stats['strategy'][strategy]['max_drawdown'])\n", 173 | "# Maximum drawdown start and end\n", 174 | "print(stats['strategy'][strategy]['drawdown_start'])\n", 175 | "print(stats['strategy'][strategy]['drawdown_end'])\n", 176 | "\n", 177 | "\n", 178 | "# Get strategy comparison (only relevant if multiple strategies were compared)\n", 179 | "print(stats['strategy_comparison'])\n" 180 | ] 181 | }, 182 | { 183 | "cell_type": "code", 184 | "execution_count": null, 185 | "metadata": {}, 186 | "outputs": [], 187 | "source": [ 188 | "# Load backtested trades as dataframe\n", 189 | "trades = load_backtest_data(backtest_dir)\n", 190 | "\n", 191 | "# Show value-counts per pair\n", 192 | "trades.groupby(\"pair\")[\"exit_reason\"].value_counts()" 193 | ] 194 | }, 195 | { 196 | "cell_type": "markdown", 197 | "metadata": {}, 198 | "source": [ 199 | "## Plotting daily profit / equity line" 200 | ] 201 | }, 202 | { 203 | "cell_type": "code", 204 | "execution_count": null, 205 | "metadata": {}, 206 | "outputs": [], 207 | "source": [ 208 | "# Plotting equity line (starting with 0 on day 1 and adding daily profit for each backtested day)\n", 209 | "\n", 210 | "from freqtrade.configuration import Configuration\n", 211 | "from freqtrade.data.btanalysis import load_backtest_data, load_backtest_stats\n", 212 | "import plotly.express as px\n", 213 | "import pandas as pd\n", 214 | "\n", 215 | "# strategy = 'SampleStrategy'\n", 216 | "# config = Configuration.from_files([\"user_data/config.json\"])\n", 217 | "# backtest_dir = config[\"user_data_dir\"] / \"backtest_results\"\n", 218 | "\n", 219 | "stats = load_backtest_stats(backtest_dir)\n", 220 | "strategy_stats = stats['strategy'][strategy]\n", 221 | "\n", 222 | "dates = []\n", 223 | "profits = []\n", 224 | "for date_profit in strategy_stats['daily_profit']:\n", 225 | " dates.append(date_profit[0])\n", 226 | " profits.append(date_profit[1])\n", 227 | "\n", 228 | "equity = 0\n", 229 | "equity_daily = []\n", 230 | "for daily_profit in profits:\n", 231 | " equity_daily.append(equity)\n", 232 | " equity += float(daily_profit)\n", 233 | "\n", 234 | "\n", 235 | "df = pd.DataFrame({'dates': dates,'equity_daily': equity_daily})\n", 236 | "\n", 237 | "fig = px.line(df, x=\"dates\", y=\"equity_daily\")\n", 238 | "fig.show()\n" 239 | ] 240 | }, 241 | { 242 | "cell_type": "markdown", 243 | "metadata": {}, 244 | "source": [ 245 | "### Load live trading results into a pandas dataframe\n", 246 | "\n", 247 | "In case you did already some trading and want to analyze your performance" 248 | ] 249 | }, 250 | { 251 | "cell_type": "code", 252 | "execution_count": null, 253 | "metadata": {}, 254 | "outputs": [], 255 | "source": [ 256 | "from freqtrade.data.btanalysis import load_trades_from_db\n", 257 | "\n", 258 | "# Fetch trades from database\n", 259 | "trades = load_trades_from_db(\"sqlite:///tradesv3.sqlite\")\n", 260 | "\n", 261 | "# Display results\n", 262 | "trades.groupby(\"pair\")[\"exit_reason\"].value_counts()" 263 | ] 264 | }, 265 | { 266 | "cell_type": "markdown", 267 | "metadata": {}, 268 | "source": [ 269 | "## Analyze the loaded trades for trade parallelism\n", 270 | "This can be useful to find the best `max_open_trades` parameter, when used with backtesting in conjunction with `--disable-max-market-positions`.\n", 271 | "\n", 272 | "`analyze_trade_parallelism()` returns a timeseries dataframe with an \"open_trades\" column, specifying the number of open trades for each candle." 273 | ] 274 | }, 275 | { 276 | "cell_type": "code", 277 | "execution_count": null, 278 | "metadata": {}, 279 | "outputs": [], 280 | "source": [ 281 | "from freqtrade.data.btanalysis import analyze_trade_parallelism\n", 282 | "\n", 283 | "# Analyze the above\n", 284 | "parallel_trades = analyze_trade_parallelism(trades, '5m')\n", 285 | "\n", 286 | "parallel_trades.plot()" 287 | ] 288 | }, 289 | { 290 | "cell_type": "markdown", 291 | "metadata": {}, 292 | "source": [ 293 | "## Plot results\n", 294 | "\n", 295 | "Freqtrade offers interactive plotting capabilities based on plotly." 296 | ] 297 | }, 298 | { 299 | "cell_type": "code", 300 | "execution_count": null, 301 | "metadata": {}, 302 | "outputs": [], 303 | "source": [ 304 | "from freqtrade.plot.plotting import generate_candlestick_graph\n", 305 | "# Limit graph period to keep plotly quick and reactive\n", 306 | "\n", 307 | "# Filter trades to one pair\n", 308 | "trades_red = trades.loc[trades['pair'] == pair]\n", 309 | "\n", 310 | "data_red = data['2019-06-01':'2019-06-10']\n", 311 | "# Generate candlestick graph\n", 312 | "graph = generate_candlestick_graph(pair=pair,\n", 313 | " data=data_red,\n", 314 | " trades=trades_red,\n", 315 | " indicators1=['sma20', 'ema50', 'ema55'],\n", 316 | " indicators2=['rsi', 'macd', 'macdsignal', 'macdhist']\n", 317 | " )\n", 318 | "\n", 319 | "\n" 320 | ] 321 | }, 322 | { 323 | "cell_type": "code", 324 | "execution_count": null, 325 | "metadata": {}, 326 | "outputs": [], 327 | "source": [ 328 | "# Show graph inline\n", 329 | "# graph.show()\n", 330 | "\n", 331 | "# Render graph in a seperate window\n", 332 | "graph.show(renderer=\"browser\")\n" 333 | ] 334 | }, 335 | { 336 | "cell_type": "markdown", 337 | "metadata": {}, 338 | "source": [ 339 | "## Plot average profit per trade as distribution graph" 340 | ] 341 | }, 342 | { 343 | "cell_type": "code", 344 | "execution_count": null, 345 | "metadata": {}, 346 | "outputs": [], 347 | "source": [ 348 | "import plotly.figure_factory as ff\n", 349 | "\n", 350 | "hist_data = [trades.profit_ratio]\n", 351 | "group_labels = ['profit_ratio'] # name of the dataset\n", 352 | "\n", 353 | "fig = ff.create_distplot(hist_data, group_labels, bin_size=0.01)\n", 354 | "fig.show()\n" 355 | ] 356 | }, 357 | { 358 | "cell_type": "markdown", 359 | "metadata": {}, 360 | "source": [ 361 | "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." 362 | ] 363 | } 364 | ], 365 | "metadata": { 366 | "file_extension": ".py", 367 | "kernelspec": { 368 | "display_name": "Python 3.9.7 64-bit ('trade_397')", 369 | "language": "python", 370 | "name": "python3" 371 | }, 372 | "language_info": { 373 | "codemirror_mode": { 374 | "name": "ipython", 375 | "version": 3 376 | }, 377 | "file_extension": ".py", 378 | "mimetype": "text/x-python", 379 | "name": "python", 380 | "nbconvert_exporter": "python", 381 | "pygments_lexer": "ipython3", 382 | "version": "3.9.7" 383 | }, 384 | "mimetype": "text/x-python", 385 | "name": "python", 386 | "npconvert_exporter": "python", 387 | "pygments_lexer": "ipython3", 388 | "toc": { 389 | "base_numbering": 1, 390 | "nav_menu": {}, 391 | "number_sections": true, 392 | "sideBar": true, 393 | "skip_h1_title": false, 394 | "title_cell": "Table of Contents", 395 | "title_sidebar": "Contents", 396 | "toc_cell": false, 397 | "toc_position": {}, 398 | "toc_section_display": true, 399 | "toc_window_display": false 400 | }, 401 | "varInspector": { 402 | "cols": { 403 | "lenName": 16, 404 | "lenType": 16, 405 | "lenVar": 40 406 | }, 407 | "kernels_config": { 408 | "python": { 409 | "delete_cmd_postfix": "", 410 | "delete_cmd_prefix": "del ", 411 | "library": "var_list.py", 412 | "varRefreshCmd": "print(var_dic_list())" 413 | }, 414 | "r": { 415 | "delete_cmd_postfix": ") ", 416 | "delete_cmd_prefix": "rm(", 417 | "library": "var_list.r", 418 | "varRefreshCmd": "cat(var_dic_list()) " 419 | } 420 | }, 421 | "types_to_exclude": [ 422 | "module", 423 | "function", 424 | "builtin_function_or_method", 425 | "instance", 426 | "_Feature" 427 | ], 428 | "window_display": false 429 | }, 430 | "version": 3, 431 | "vscode": { 432 | "interpreter": { 433 | "hash": "675f32a300d6d26767470181ad0b11dd4676bcce7ed1dd2ffe2fbc370c95fc7c" 434 | } 435 | } 436 | }, 437 | "nbformat": 4, 438 | "nbformat_minor": 4 439 | } 440 | -------------------------------------------------------------------------------- /user_data/strategies/NostalgiaForInfinityX/blacklist-binance.json: -------------------------------------------------------------------------------- 1 | { 2 | "exchange": { 3 | "pair_blacklist": [ 4 | // Exchange 5 | "(BNB)/.*", 6 | "(1000.*).*/.*", 7 | // Leverage 8 | ".*(_PREMIUM|BEAR|BULL|HALF|HEDGE|UP|DOWN|[1235][SL])/.*", 9 | // Fiat 10 | "(ARS|AUD|BIDR|BRZ|BRL|CAD|CHF|EUR|GBP|HKD|IDRT|JPY|NGN|PLN|RON|RUB|SGD|TRY|UAH|USD|ZAR)/.*", 11 | // Stable 12 | "(AEUR|FDUSD|BUSD|CUSD|CUSDT|DAI|PAXG|SUSD|TUSD|USDC|USDN|USDP|USDT|VAI|UST|USTC|AUSD)/.*", 13 | // FAN 14 | "(ACM|AFA|ALA|ALL|ALPINE|APL|ASR|ATM|BAR|CAI|CHZ|CITY|FOR|GAL|GOZ|IBFK|JUV|LEG|LOCK-1|NAVI|NMR|NOV|PFL|PSG|ROUSH|STV|TH|TRA|UCH|UFC|YBO)/.*", 15 | // Others 16 | "(1EARTH|ILA|BOBA|CWAR|OMG|DMTR|MLS|TORN|LUNA|BTS|QKC|ACA|FTT|SRM|YFII|SNM|ANC|AION|MIR|WABI|QLC|NEBL|AUTO|VGX|DREP|PNT|PERL|LOOM|ID|NULS|TOMO|WTC|1000SATS|ORDI|XMR|ANT|MULTI|VAI|DREP|MOB|PNT|BTCDOM|WAVES|WNXM|XEM|ZEC|ELF|ARK|MDX|BETA|KP3R|AKRO|AMB|BOND|FIRO|OAX|EPX|OOKI|ONDO|TRUMP|MAGA|MAGAETH|TREMP|BODEN|STRUMP|TOOKER|TMANIA|BOBBY|BABYTRUMP|PTTRUMP|DTI|TRUMPIE|MAGAPEPE|PEPEMAGA|HARD|MBL|GAL|DOCK|POLS|CTXC|JASMY|CVX|BAL|SUN|SNT|CREAM|REN|LINA|REEF|UNFI|IRIS|CVP)/.*" 17 | ] 18 | } 19 | } 20 | -------------------------------------------------------------------------------- /user_data/strategies/NostalgiaForInfinityX/pairlist-volume-binance-usdt.json: -------------------------------------------------------------------------------- 1 | { 2 | "pairlists": [ 3 | { 4 | "method": "VolumePairList", 5 | "number_assets": 100, 6 | "sort_key": "quoteVolume", 7 | "refresh_period": 1800 8 | }, 9 | { "method": "FullTradesFilter" }, 10 | { "method": "AgeFilter", "min_days_listed": 30 }, 11 | { 12 | "method": "PriceFilter", 13 | "low_price_ratio": 0.003 14 | }, 15 | { 16 | "method": "SpreadFilter", 17 | "max_spread_ratio": 0.005 18 | }, 19 | // { 20 | // "method": "RangeStabilityFilter", 21 | // "lookback_days": 3, 22 | // "min_rate_of_change": 0.03, 23 | // "refresh_period": 1800 24 | // }, 25 | // { 26 | // "method": "VolatilityFilter", 27 | // "lookback_days": 3, 28 | // "min_volatility": 0.01, 29 | // "max_volatility": 0.75, 30 | // "refresh_period": 43200 31 | // }, 32 | { 33 | "method": "VolumePairList", 34 | "number_assets": 80, 35 | "sort_key": "quoteVolume" 36 | }, 37 | // { "method": "ShuffleFilter" } 38 | ] 39 | } 40 | -------------------------------------------------------------------------------- /user_data/strategies/SampleStrategy.py: -------------------------------------------------------------------------------- 1 | # pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement 2 | # flake8: noqa: F401 3 | # isort: skip_file 4 | # --- Do not remove these libs --- 5 | import numpy as np # noqa 6 | import pandas as pd # noqa 7 | from pandas import DataFrame 8 | from typing import Optional, Union 9 | 10 | from freqtrade.strategy import (BooleanParameter, CategoricalParameter, DecimalParameter, 11 | IStrategy, IntParameter) 12 | 13 | # -------------------------------- 14 | # Add your lib to import here 15 | import talib.abstract as ta 16 | import freqtrade.vendor.qtpylib.indicators as qtpylib 17 | 18 | 19 | # This class is a sample. Feel free to customize it. 20 | class SampleStrategy(IStrategy): 21 | """ 22 | This is a sample strategy to inspire you. 23 | More information in https://www.freqtrade.io/en/latest/strategy-customization/ 24 | 25 | You can: 26 | :return: a Dataframe with all mandatory indicators for the strategies 27 | - Rename the class name (Do not forget to update class_name) 28 | - Add any methods you want to build your strategy 29 | - Add any lib you need to build your strategy 30 | 31 | You must keep: 32 | - the lib in the section "Do not remove these libs" 33 | - the methods: populate_indicators, populate_entry_trend, populate_exit_trend 34 | You should keep: 35 | - timeframe, minimal_roi, stoploss, trailing_* 36 | """ 37 | # Strategy interface version - allow new iterations of the strategy interface. 38 | # Check the documentation or the Sample strategy to get the latest version. 39 | INTERFACE_VERSION = 3 40 | 41 | # Can this strategy go short? 42 | can_short: bool = False 43 | 44 | # Minimal ROI designed for the strategy. 45 | # This attribute will be overridden if the config file contains "minimal_roi". 46 | minimal_roi = { 47 | "60": 0.01, 48 | "30": 0.02, 49 | "0": 0.04 50 | } 51 | 52 | # Optimal stoploss designed for the strategy. 53 | # This attribute will be overridden if the config file contains "stoploss". 54 | stoploss = -0.10 55 | 56 | # Trailing stoploss 57 | trailing_stop = False 58 | # trailing_only_offset_is_reached = False 59 | # trailing_stop_positive = 0.01 60 | # trailing_stop_positive_offset = 0.0 # Disabled / not configured 61 | 62 | # Optimal timeframe for the strategy. 63 | timeframe = '5m' 64 | 65 | # Run "populate_indicators()" only for new candle. 66 | process_only_new_candles = True 67 | 68 | # These values can be overridden in the config. 69 | use_exit_signal = True 70 | exit_profit_only = False 71 | ignore_roi_if_entry_signal = False 72 | 73 | # Hyperoptable parameters 74 | buy_rsi = IntParameter(low=1, high=50, default=30, space='buy', optimize=True, load=True) 75 | sell_rsi = IntParameter(low=50, high=100, default=70, space='sell', optimize=True, load=True) 76 | short_rsi = IntParameter(low=51, high=100, default=70, space='sell', optimize=True, load=True) 77 | exit_short_rsi = IntParameter(low=1, high=50, default=30, space='buy', optimize=True, load=True) 78 | 79 | # Number of candles the strategy requires before producing valid signals 80 | startup_candle_count: int = 30 81 | 82 | # Optional order type mapping. 83 | order_types = { 84 | 'entry': 'limit', 85 | 'exit': 'limit', 86 | 'stoploss': 'market', 87 | 'stoploss_on_exchange': False 88 | } 89 | 90 | # Optional order time in force. 91 | order_time_in_force = { 92 | 'entry': 'GTC', 93 | 'exit': 'GTC' 94 | } 95 | 96 | plot_config = { 97 | 'main_plot': { 98 | 'tema': {}, 99 | 'sar': {'color': 'white'}, 100 | }, 101 | 'subplots': { 102 | "MACD": { 103 | 'macd': {'color': 'blue'}, 104 | 'macdsignal': {'color': 'orange'}, 105 | }, 106 | "RSI": { 107 | 'rsi': {'color': 'red'}, 108 | } 109 | } 110 | } 111 | 112 | def informative_pairs(self): 113 | """ 114 | Define additional, informative pair/interval combinations to be cached from the exchange. 115 | These pair/interval combinations are non-tradeable, unless they are part 116 | of the whitelist as well. 117 | For more information, please consult the documentation 118 | :return: List of tuples in the format (pair, interval) 119 | Sample: return [("ETH/USDT", "5m"), 120 | ("BTC/USDT", "15m"), 121 | ] 122 | """ 123 | return [] 124 | 125 | def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: 126 | """ 127 | Adds several different TA indicators to the given DataFrame 128 | 129 | Performance Note: For the best performance be frugal on the number of indicators 130 | you are using. Let uncomment only the indicator you are using in your strategies 131 | or your hyperopt configuration, otherwise you will waste your memory and CPU usage. 132 | :param dataframe: Dataframe with data from the exchange 133 | :param metadata: Additional information, like the currently traded pair 134 | :return: a Dataframe with all mandatory indicators for the strategies 135 | """ 136 | 137 | # Momentum Indicators 138 | # ------------------------------------ 139 | 140 | # ADX 141 | dataframe['adx'] = ta.ADX(dataframe) 142 | 143 | # # Plus Directional Indicator / Movement 144 | # dataframe['plus_dm'] = ta.PLUS_DM(dataframe) 145 | # dataframe['plus_di'] = ta.PLUS_DI(dataframe) 146 | 147 | # # Minus Directional Indicator / Movement 148 | # dataframe['minus_dm'] = ta.MINUS_DM(dataframe) 149 | # dataframe['minus_di'] = ta.MINUS_DI(dataframe) 150 | 151 | # # Aroon, Aroon Oscillator 152 | # aroon = ta.AROON(dataframe) 153 | # dataframe['aroonup'] = aroon['aroonup'] 154 | # dataframe['aroondown'] = aroon['aroondown'] 155 | # dataframe['aroonosc'] = ta.AROONOSC(dataframe) 156 | 157 | # # Awesome Oscillator 158 | # dataframe['ao'] = qtpylib.awesome_oscillator(dataframe) 159 | 160 | # # Keltner Channel 161 | # keltner = qtpylib.keltner_channel(dataframe) 162 | # dataframe["kc_upperband"] = keltner["upper"] 163 | # dataframe["kc_lowerband"] = keltner["lower"] 164 | # dataframe["kc_middleband"] = keltner["mid"] 165 | # dataframe["kc_percent"] = ( 166 | # (dataframe["close"] - dataframe["kc_lowerband"]) / 167 | # (dataframe["kc_upperband"] - dataframe["kc_lowerband"]) 168 | # ) 169 | # dataframe["kc_width"] = ( 170 | # (dataframe["kc_upperband"] - dataframe["kc_lowerband"]) / dataframe["kc_middleband"] 171 | # ) 172 | 173 | # # Ultimate Oscillator 174 | # dataframe['uo'] = ta.ULTOSC(dataframe) 175 | 176 | # # Commodity Channel Index: values [Oversold:-100, Overbought:100] 177 | # dataframe['cci'] = ta.CCI(dataframe) 178 | 179 | # RSI 180 | dataframe['rsi'] = ta.RSI(dataframe) 181 | 182 | # # Inverse Fisher transform on RSI: values [-1.0, 1.0] (https://goo.gl/2JGGoy) 183 | # rsi = 0.1 * (dataframe['rsi'] - 50) 184 | # dataframe['fisher_rsi'] = (np.exp(2 * rsi) - 1) / (np.exp(2 * rsi) + 1) 185 | 186 | # # Inverse Fisher transform on RSI normalized: values [0.0, 100.0] (https://goo.gl/2JGGoy) 187 | # dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1) 188 | 189 | # # Stochastic Slow 190 | # stoch = ta.STOCH(dataframe) 191 | # dataframe['slowd'] = stoch['slowd'] 192 | # dataframe['slowk'] = stoch['slowk'] 193 | 194 | # Stochastic Fast 195 | stoch_fast = ta.STOCHF(dataframe) 196 | dataframe['fastd'] = stoch_fast['fastd'] 197 | dataframe['fastk'] = stoch_fast['fastk'] 198 | 199 | # # Stochastic RSI 200 | # Please read https://github.com/freqtrade/freqtrade/issues/2961 before using this. 201 | # STOCHRSI is NOT aligned with tradingview, which may result in non-expected results. 202 | # stoch_rsi = ta.STOCHRSI(dataframe) 203 | # dataframe['fastd_rsi'] = stoch_rsi['fastd'] 204 | # dataframe['fastk_rsi'] = stoch_rsi['fastk'] 205 | 206 | # MACD 207 | macd = ta.MACD(dataframe) 208 | dataframe['macd'] = macd['macd'] 209 | dataframe['macdsignal'] = macd['macdsignal'] 210 | dataframe['macdhist'] = macd['macdhist'] 211 | 212 | # MFI 213 | dataframe['mfi'] = ta.MFI(dataframe) 214 | 215 | # # ROC 216 | # dataframe['roc'] = ta.ROC(dataframe) 217 | 218 | # Overlap Studies 219 | # ------------------------------------ 220 | 221 | # Bollinger Bands 222 | bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2) 223 | dataframe['bb_lowerband'] = bollinger['lower'] 224 | dataframe['bb_middleband'] = bollinger['mid'] 225 | dataframe['bb_upperband'] = bollinger['upper'] 226 | dataframe["bb_percent"] = ( 227 | (dataframe["close"] - dataframe["bb_lowerband"]) / 228 | (dataframe["bb_upperband"] - dataframe["bb_lowerband"]) 229 | ) 230 | dataframe["bb_width"] = ( 231 | (dataframe["bb_upperband"] - dataframe["bb_lowerband"]) / dataframe["bb_middleband"] 232 | ) 233 | 234 | # Bollinger Bands - Weighted (EMA based instead of SMA) 235 | # weighted_bollinger = qtpylib.weighted_bollinger_bands( 236 | # qtpylib.typical_price(dataframe), window=20, stds=2 237 | # ) 238 | # dataframe["wbb_upperband"] = weighted_bollinger["upper"] 239 | # dataframe["wbb_lowerband"] = weighted_bollinger["lower"] 240 | # dataframe["wbb_middleband"] = weighted_bollinger["mid"] 241 | # dataframe["wbb_percent"] = ( 242 | # (dataframe["close"] - dataframe["wbb_lowerband"]) / 243 | # (dataframe["wbb_upperband"] - dataframe["wbb_lowerband"]) 244 | # ) 245 | # dataframe["wbb_width"] = ( 246 | # (dataframe["wbb_upperband"] - dataframe["wbb_lowerband"]) / 247 | # dataframe["wbb_middleband"] 248 | # ) 249 | 250 | # # EMA - Exponential Moving Average 251 | # dataframe['ema3'] = ta.EMA(dataframe, timeperiod=3) 252 | # dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5) 253 | # dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10) 254 | # dataframe['ema21'] = ta.EMA(dataframe, timeperiod=21) 255 | # dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50) 256 | # dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100) 257 | 258 | # # SMA - Simple Moving Average 259 | # dataframe['sma3'] = ta.SMA(dataframe, timeperiod=3) 260 | # dataframe['sma5'] = ta.SMA(dataframe, timeperiod=5) 261 | # dataframe['sma10'] = ta.SMA(dataframe, timeperiod=10) 262 | # dataframe['sma21'] = ta.SMA(dataframe, timeperiod=21) 263 | # dataframe['sma50'] = ta.SMA(dataframe, timeperiod=50) 264 | # dataframe['sma100'] = ta.SMA(dataframe, timeperiod=100) 265 | 266 | # Parabolic SAR 267 | dataframe['sar'] = ta.SAR(dataframe) 268 | 269 | # TEMA - Triple Exponential Moving Average 270 | dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9) 271 | 272 | # Cycle Indicator 273 | # ------------------------------------ 274 | # Hilbert Transform Indicator - SineWave 275 | hilbert = ta.HT_SINE(dataframe) 276 | dataframe['htsine'] = hilbert['sine'] 277 | dataframe['htleadsine'] = hilbert['leadsine'] 278 | 279 | # Pattern Recognition - Bullish candlestick patterns 280 | # ------------------------------------ 281 | # # Hammer: values [0, 100] 282 | # dataframe['CDLHAMMER'] = ta.CDLHAMMER(dataframe) 283 | # # Inverted Hammer: values [0, 100] 284 | # dataframe['CDLINVERTEDHAMMER'] = ta.CDLINVERTEDHAMMER(dataframe) 285 | # # Dragonfly Doji: values [0, 100] 286 | # dataframe['CDLDRAGONFLYDOJI'] = ta.CDLDRAGONFLYDOJI(dataframe) 287 | # # Piercing Line: values [0, 100] 288 | # dataframe['CDLPIERCING'] = ta.CDLPIERCING(dataframe) # values [0, 100] 289 | # # Morningstar: values [0, 100] 290 | # dataframe['CDLMORNINGSTAR'] = ta.CDLMORNINGSTAR(dataframe) # values [0, 100] 291 | # # Three White Soldiers: values [0, 100] 292 | # dataframe['CDL3WHITESOLDIERS'] = ta.CDL3WHITESOLDIERS(dataframe) # values [0, 100] 293 | 294 | # Pattern Recognition - Bearish candlestick patterns 295 | # ------------------------------------ 296 | # # Hanging Man: values [0, 100] 297 | # dataframe['CDLHANGINGMAN'] = ta.CDLHANGINGMAN(dataframe) 298 | # # Shooting Star: values [0, 100] 299 | # dataframe['CDLSHOOTINGSTAR'] = ta.CDLSHOOTINGSTAR(dataframe) 300 | # # Gravestone Doji: values [0, 100] 301 | # dataframe['CDLGRAVESTONEDOJI'] = ta.CDLGRAVESTONEDOJI(dataframe) 302 | # # Dark Cloud Cover: values [0, 100] 303 | # dataframe['CDLDARKCLOUDCOVER'] = ta.CDLDARKCLOUDCOVER(dataframe) 304 | # # Evening Doji Star: values [0, 100] 305 | # dataframe['CDLEVENINGDOJISTAR'] = ta.CDLEVENINGDOJISTAR(dataframe) 306 | # # Evening Star: values [0, 100] 307 | # dataframe['CDLEVENINGSTAR'] = ta.CDLEVENINGSTAR(dataframe) 308 | 309 | # Pattern Recognition - Bullish/Bearish candlestick patterns 310 | # ------------------------------------ 311 | # # Three Line Strike: values [0, -100, 100] 312 | # dataframe['CDL3LINESTRIKE'] = ta.CDL3LINESTRIKE(dataframe) 313 | # # Spinning Top: values [0, -100, 100] 314 | # dataframe['CDLSPINNINGTOP'] = ta.CDLSPINNINGTOP(dataframe) # values [0, -100, 100] 315 | # # Engulfing: values [0, -100, 100] 316 | # dataframe['CDLENGULFING'] = ta.CDLENGULFING(dataframe) # values [0, -100, 100] 317 | # # Harami: values [0, -100, 100] 318 | # dataframe['CDLHARAMI'] = ta.CDLHARAMI(dataframe) # values [0, -100, 100] 319 | # # Three Outside Up/Down: values [0, -100, 100] 320 | # dataframe['CDL3OUTSIDE'] = ta.CDL3OUTSIDE(dataframe) # values [0, -100, 100] 321 | # # Three Inside Up/Down: values [0, -100, 100] 322 | # dataframe['CDL3INSIDE'] = ta.CDL3INSIDE(dataframe) # values [0, -100, 100] 323 | 324 | # # Chart type 325 | # # ------------------------------------ 326 | # # Heikin Ashi Strategy 327 | # heikinashi = qtpylib.heikinashi(dataframe) 328 | # dataframe['ha_open'] = heikinashi['open'] 329 | # dataframe['ha_close'] = heikinashi['close'] 330 | # dataframe['ha_high'] = heikinashi['high'] 331 | # dataframe['ha_low'] = heikinashi['low'] 332 | 333 | # Retrieve best bid and best ask from the orderbook 334 | # ------------------------------------ 335 | """ 336 | # first check if dataprovider is available 337 | if self.dp: 338 | if self.dp.runmode.value in ('live', 'dry_run'): 339 | ob = self.dp.orderbook(metadata['pair'], 1) 340 | dataframe['best_bid'] = ob['bids'][0][0] 341 | dataframe['best_ask'] = ob['asks'][0][0] 342 | """ 343 | 344 | return dataframe 345 | 346 | def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: 347 | """ 348 | Based on TA indicators, populates the entry signal for the given dataframe 349 | :param dataframe: DataFrame 350 | :param metadata: Additional information, like the currently traded pair 351 | :return: DataFrame with entry columns populated 352 | """ 353 | dataframe.loc[ 354 | ( 355 | # Signal: RSI crosses above 30 356 | (qtpylib.crossed_above(dataframe['rsi'], self.buy_rsi.value)) & 357 | (dataframe['tema'] <= dataframe['bb_middleband']) & # Guard: tema below BB middle 358 | (dataframe['tema'] > dataframe['tema'].shift(1)) & # Guard: tema is raising 359 | (dataframe['volume'] > 0) # Make sure Volume is not 0 360 | ), 361 | 'enter_long'] = 1 362 | 363 | dataframe.loc[ 364 | ( 365 | # Signal: RSI crosses above 70 366 | (qtpylib.crossed_above(dataframe['rsi'], self.short_rsi.value)) & 367 | (dataframe['tema'] > dataframe['bb_middleband']) & # Guard: tema above BB middle 368 | (dataframe['tema'] < dataframe['tema'].shift(1)) & # Guard: tema is falling 369 | (dataframe['volume'] > 0) # Make sure Volume is not 0 370 | ), 371 | 'enter_short'] = 1 372 | 373 | return dataframe 374 | 375 | def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: 376 | """ 377 | Based on TA indicators, populates the exit signal for the given dataframe 378 | :param dataframe: DataFrame 379 | :param metadata: Additional information, like the currently traded pair 380 | :return: DataFrame with exit columns populated 381 | """ 382 | dataframe.loc[ 383 | ( 384 | # Signal: RSI crosses above 70 385 | (qtpylib.crossed_above(dataframe['rsi'], self.sell_rsi.value)) & 386 | (dataframe['tema'] > dataframe['bb_middleband']) & # Guard: tema above BB middle 387 | (dataframe['tema'] < dataframe['tema'].shift(1)) & # Guard: tema is falling 388 | (dataframe['volume'] > 0) # Make sure Volume is not 0 389 | ), 390 | 391 | 'exit_long'] = 1 392 | 393 | dataframe.loc[ 394 | ( 395 | # Signal: RSI crosses above 30 396 | (qtpylib.crossed_above(dataframe['rsi'], self.exit_short_rsi.value)) & 397 | # Guard: tema below BB middle 398 | (dataframe['tema'] <= dataframe['bb_middleband']) & 399 | (dataframe['tema'] > dataframe['tema'].shift(1)) & # Guard: tema is raising 400 | (dataframe['volume'] > 0) # Make sure Volume is not 0 401 | ), 402 | 'exit_short'] = 1 403 | 404 | return dataframe 405 | --------------------------------------------------------------------------------