freqtrade / freqtrade-strategies

Free trading strategies for Freqtrade bot

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Freqtrade strategies

This Git repo contains free buy/sell strategies for Freqtrade.

All strategies should work with a freqtrade version of 2022.4 or newer.

Disclaimer

These strategies are for educational purposes only. Do not risk money which you are afraid to lose. USE THE SOFTWARE AT YOUR OWN RISK. THE AUTHORS AND ALL AFFILIATES ASSUME NO RESPONSIBILITY FOR YOUR TRADING RESULTS.

Always start by testing strategies with a backtesting then run the trading bot in Dry-run. Do not engage money before you understand how it works and what profit/loss you should expect.

We strongly recommend you to have coding and Python knowledge. Do not hesitate to read the source code and understand the mechanism of this bot.

Table of Content

Free trading strategies

Value below are result from backtesting from 2018-01-10 to 2018-01-30 and
exit_profit_only enabled. More detail on each strategy page.

Strategy Buy count AVG profit % Total profit AVG duration Backtest period
Strategy 001 55 0.05 0.00012102 476.1 2018-01-10 to 2018-01-30
Strategy 002 9 3.21 0.00114807 189.4 2018-01-10 to 2018-01-30
Strategy 003 14 1.47 0.00081740 227.5 2018-01-10 to 2018-01-30
Strategy 004 37 0.69 0.00102128 367.3 2018-01-10 to 2018-01-30
Strategy 005 180 1.16 0.00827589 156.2 2018-01-10 to 2018-01-30

Strategies from this repo are free to use. Feel free to update them to your likings. Most of them were designed from Hyperopt calculations.

Some only work in specific market conditions, while others are more "general purpose" strategies. It's noteworthy that depending on the exchange and Pairs used, further optimization can bring better results.

Please keep in mind, results will heavily depend on the pairs, timeframe and timerange used to backtest - so please run your own backtests that mirror your usecase, to evaluate each strategy for yourself.

The results above should serve as a general outline to demonstrate the number of trades to expect. Actual performance will be different based on various factors.

Share your own strategies and contribute to this repo

Feel free to send your strategies, comments, optimizations and pull requests via an Issue ticket or as a Pull request enhancing this repository.

FAQ

What is Freqtrade?

Freqtrade Freqtrade is a free and open source crypto trading bot written in Python. It is designed to support all major exchanges and be controlled via Telegram. It contains backtesting, plotting and money management tools as well as strategy optimization by machine learning.

What includes these strategies?

Each Strategies includes:

  • Minimal ROI: Minimal ROI optimized for the strategy.
  • Stoploss: Optimimal stoploss.
  • Buy signals: Result from Hyperopt or based on exisiting trading strategies.
  • Sell signals: Result from Hyperopt or based on exisiting trading strategies.
  • Indicators: Includes the indicators required to run the strategy.

Best backtest multiple strategies with the exchange and pairs you're interrested in, and finetune the strategy to the markets you're trading.

How to install a strategy?

First you need a working Freqtrade.

Once you have the bot on the right version, follow this steps:

  1. Select the strategy you want. All strategies of the repo are into user_data/strategies
  2. Copy the strategy file
  3. Paste it into your user_data/strategies folder
  4. Run the bot with the parameter --strategy <STRATEGY CLASS NAME> (ex: freqtrade trade --strategy Strategy001)

More information about backtesting and strategy customization.

How to test a strategy?

Let assume you have selected the strategy strategy001.py:

Simple backtesting

freqtrade backtesting --strategy Strategy001

Refresh your test data

freqtrade download-data --days 100

Note: Generally, it's recommended to use static backtest data (from a defined period of time) for comparable results.

Please check out the official backtesting documentation for more information.

About

Free trading strategies for Freqtrade bot

License:GNU General Public License v3.0


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