This Git repo contains free buy/sell strategies for Freqtrade.
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.
Value below are result from backtesting from 2018-01-10 to 2018-01-30 and
ask_strategy.sell_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. 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.
Feel free to send your strategies, comments, optimizations and pull requests via an Issue ticket or as a Pull request enhancing this repository.
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.
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.
First you need a working Freqtrade.
Once you have the bot on the right version, follow this steps:
- Select the strategy you want. All strategies of the repo are into user_data/strategies
- Copy the strategy file
- Paste it into your
user_data/strategiesfolder - Run the bot with the parameter
--strategy <STRATEGY CLASS NAME>(ex:freqtrade trade --strategy Strategy001)
More information about backtesting and strategy customization.
Let assume you have selected the strategy strategy001.py:
freqtrade backtesting --strategy Strategy001freqtrade download-data --days 100Note: 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.