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webappcreations / freqtrade-strategies

Free trading strategies for Freqtrade bot

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Freqtrade strategies

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

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.

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.

Table of Content

Free trading strategies

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

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

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

Contributes

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

Strategy requests

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.

FAQ

What is Freqtrade?

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

What includes these strategies?

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

How were tested the strategies?

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

Period 1: From 2017-11-19 to 2017-12-20

  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).

Period 2: From 2017-12-19 to 2017-01-20

  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).

How to install a strategy?

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)

How to test a strategy?

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

Which coins were tested?

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)

Pair Tested
BTC_ADA Yes
BTC_NEO Yes
BTC_NXT Yes
BTC_MCO Yes
BTC_ETH Yes
BTC_BCC Yes
BTC_VOX Yes
BTC_GUP Yes
BTC_SC Yes
BTC_VTC Yes
BTC_STRAT Yes
BTC_OMG Yes
BTC_OK Yes
BTC_EDG Yes
BTC_STORJ Yes
BTC_EMC2 Yes
BTC_XLM Yes
BTC_LSK Yes
BTC_SYS Yes
BTC_POWR Yes
BTC_PAY Yes
BTC_DGB Yes
BTC_ETC Yes
BTC_XRP Yes
BTC_LTC Yes
BTC_IOP Yes
BTC_RCN Yes
BTC_BTG Yes
BTC_MONA Yes
BTC_SALT Yes
BTC_DASH Yes
BTC_QTUM Yes
BTC_CVC Yes
BTC_KMD Yes
BTC_XEM Yes
BTC_XMR Yes
BTC_ZEC Yes
BTC_WAVES Yes
BTC_PIVX Yes
BTC_XZC Yes
BTC_DOGE No, this pair is blacklisted

Can I have your configuration file?

You will find them into user_data/ folder.

Can I have your datasets?

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

How did you build dataset?

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

Offer me a coffee

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

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Free trading strategies for Freqtrade bot

License:GNU General Public License v3.0

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Language:Python 100.0%