This Git repo contains free buy/sell strategies for Freqtrade >= 0.16.0.

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.

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

• Free trading strategies
• Contributes
• FAQ
  • What is Freqtrade?
  • What includes these strategies?
  • How were tested the strategies?
  • How to install a strategy?
  • How to test a strategy?
  • Which coins were tested?
  • Can I have your configuration file?
  • Can I have your dataset?
  • How did you build dataset?
  • How to create/optimize a strategy?
• Offer me a coffee

Value below are result from backtesting from 2017-12-19 to 2017-01-20 and
experimental.sell_profit_only enabled. More detail on each strategy page.

Strategies from this repo are free to use and feel free to update them. Most of them were designed from Hyperopt calculations.

Feel free to send your comments, optimizations and requests via an Issue ticket.

Are you looking to implement a new strategy, or one found on atrading Forum/Chan?
You can request it via Issue ticket. Please follow the template questions. Request that does not follow the template will be removed. I cannot promise to implement all of them, but will do my best to help.

Freqtrade is a Simple High frequency trading bot for crypto currencies designed to support multi exchanges and be controlled via Telegram built by gcarq@.

This bot is similar other trading bot like Gekko, and Zenbot

Each Strategies includes:

• Minimal ROI: Minimal ROI optimized for the strategy.
• Stoploss: Optimimal stoploss calculated based on hyperopt result.
• Buy Strategy: Result from Hyperopt or based on exisiting trading strategies.
• Sell Strategy
• Indicators: Includes the indicators required to run the strategy.
• Hyperopt configuration: To tune the strategy parameters.
• Backtesting results

All strategies are tested with the dataset from this repo. The data set is located into user_data/data folder.
For each strategies, I run backtests for 2 Period and 2 parameters: experimental.sell_profit_only enabled and
experimental.sell_profit_only disabled

1. experimental.sell_profit_only at true (Config file user_data/config-profit-on.json).
2. experimental.sell_profit_only at false (Config file user_data/config-profit-off.json).

1. experimental.sell_profit_only at true (Config file user_data/config-profit-on.json).
2. experimental.sell_profit_only at false (Config file user_data/config-profit-off.json).

First you need a working Freqtrade in version >= 0.16.0.

Note: This version is not merged yet but you can find into the branch feature/custom_strategy.

git clone https://github.com/gcarq/freqtrade.git
git checkout feature/custom_strategy

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](https://github.com/glonlas/freqtrade-strategies/tree/feature/custom_strategy/user_data/strategies)
2. Copy the strategy file
3. Paste it into your user_data/strategies folder
4. Run the bot with the parameter -s <STRATEGY_FILE_NAME_WITHOUT_.py> (ex: python3 ./freqtrade/main.py -s strategy001)

Let assume you have selected the strategy strategy-001.py:

Simple backtesting

python3 ./freqtrade/main.py -s strategy-001 backtesting --realistic-simulation

Refresh your test data

python3 ./freqtrade/main.py -s strategy-001 backtesting --realistic-simulation -r

Test with live data

python3 ./freqtrade/main.py -s strategy-001 backtesting --realistic-simulation -l

You will find the list of coin tested into the configuration files (user_data/config-profit-on.json and user_data/config-profit-off.json)

You will find them into user_data/ folder.

Yes of course! Datasets are into user_data/data folder. Download and use them.

I am using data collected from Bittrex and run the script scripts/extract_data.py

python3 scripts/extract_data.py -f user_data/data/complete_data -d user_data/data/2017-11-19_2017-12-19 -s 2017-11-19 -e 2017-12-20
python3 scripts/extract_data.py -f user_data/data/complete_data -d user_data/data/2017-12-19_2018-01-19 -s 2017-12-19 -e 2018-01-20

This repo is made for you to improve your trading strategies. If you are happy with the result of your strategy, feel free to offer me a coffee :)

• BTC: 1KouEQdEKGiFGvm9iCb5K9pkUqnsASqmGS
• ETH: 0x767D8AfB3B31131cBbf5b7318D2046996c9a40f2
• LTC: LXFPwMs38DMj6ecD4xWEPnWjNAjp78uNZM