[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-79140":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":9,"totalLinesOfCode":9,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":9,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":9,"rankLanguage":9,"license":9,"archived":22,"fork":22,"defaultBranch":23,"hasWiki":22,"hasPages":22,"topics":24,"createdAt":9,"pushedAt":9,"updatedAt":30,"readmeContent":31,"aiSummary":32,"trendingCount":16,"starSnapshotCount":16,"syncStatus":33,"lastSyncTime":34,"discoverSource":35},79140,"freqtrade-strategies","freqtrade\u002Ffreqtrade-strategies","freqtrade","Free trading strategies for Freqtrade bot",null,"https:\u002F\u002Fgithub.com\u002Ffreqtrade\u002Ffreqtrade-strategies","Python",5225,1411,172,11,0,12,28,50,36,40.45,false,"main",[5,25,26,27,28,29],"bitcoin","cryptocurrency","trading-bot","trading-strategies","trading","2026-06-12 02:03:49","# Freqtrade strategies\n\nThis Git repo contains free buy\u002Fsell strategies for [Freqtrade](https:\u002F\u002Fgithub.com\u002Ffreqtrade\u002Ffreqtrade).\n\nAll strategies should work with a freqtrade version of 2022.4 or newer.\n\n## Disclaimer\n\nThese strategies are for educational purposes only. Do not risk money \nwhich you are afraid to lose. USE THE SOFTWARE AT YOUR OWN RISK. THE \nAUTHORS AND ALL AFFILIATES ASSUME NO RESPONSIBILITY FOR YOUR TRADING \nRESULTS. \n\nAlways start by testing strategies with a backtesting then run the \ntrading bot in Dry-run. Do not engage money before you understand how \nit works and what profit\u002Floss you should expect.\n\nWe strongly recommend you to have coding and Python knowledge. Do not \nhesitate to read the source code and understand the mechanism of this \nbot.\n\n## Table of Content\n\n- [Free trading strategies](#free-trading-strategies)\n- [Contribute](#share-your-own-strategies-and-contribute-to-this-repo)\n- [FAQ](#faq)\n    - [What is Freqtrade?](#what-is-freqtrade)\n    - [What includes these strategies?](#what-includes-these-strategies)\n    - [How to install a strategy?](#how-to-install-a-strategy)\n    - [How to test a strategy?](#how-to-test-a-strategy)\n    - [How to create\u002Foptimize a strategy?](https:\u002F\u002Fwww.freqtrade.io\u002Fen\u002Flatest\u002Fstrategy-customization\u002F)\n\n## Free trading strategies\n\nValue below are result from backtesting from 2018-01-10 to 2018-01-30 and  \n`exit_profit_only` enabled. More detail on each strategy page.\n\n|  Strategy | Buy count | AVG profit % | Total profit | AVG duration | Backtest period |\n|-----------|-----------|--------------|--------------|--------------|-----------------|\n| [Strategy 001](https:\u002F\u002Fgithub.com\u002Ffreqtrade\u002Ffreqtrade-strategies\u002Fblob\u002Fmain\u002Fuser_data\u002Fstrategies\u002FStrategy001.py) | 55 | 0.05 | 0.00012102 |  476.1 | 2018-01-10 to 2018-01-30 |\n| [Strategy 002](https:\u002F\u002Fgithub.com\u002Ffreqtrade\u002Ffreqtrade-strategies\u002Fblob\u002Fmain\u002Fuser_data\u002Fstrategies\u002FStrategy002.py) | 9 | 3.21 | 0.00114807 |  189.4 | 2018-01-10 to 2018-01-30 |\n| [Strategy 003](https:\u002F\u002Fgithub.com\u002Ffreqtrade\u002Ffreqtrade-strategies\u002Fblob\u002Fmain\u002Fuser_data\u002Fstrategies\u002FStrategy003.py) | 14 | 1.47 | 0.00081740 |  227.5 | 2018-01-10 to 2018-01-30 | \n| [Strategy 004](https:\u002F\u002Fgithub.com\u002Ffreqtrade\u002Ffreqtrade-strategies\u002Fblob\u002Fmain\u002Fuser_data\u002Fstrategies\u002FStrategy004.py) | 37 | 0.69 | 0.00102128 |  367.3 | 2018-01-10 to 2018-01-30 | \n| [Strategy 005](https:\u002F\u002Fgithub.com\u002Ffreqtrade\u002Ffreqtrade-strategies\u002Fblob\u002Fmain\u002Fuser_data\u002Fstrategies\u002FStrategy005.py) | 180 | 1.16 | 0.00827589 |  156.2 | 2018-01-10 to 2018-01-30 |\n\nStrategies from this repo are free to use. Feel free to update them to your likings.\nMost of them  were designed from Hyperopt calculations.\n\nSome only work in specific market conditions, while others are more \"general purpose\" strategies.\nIt's noteworthy that depending on the exchange and Pairs used, further optimization can bring better results.\n\nPlease 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.\n\nThe 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.\n\n## Share your own strategies and contribute to this repo\n\nFeel free to send your strategies, comments, optimizations and pull requests via an \n[Issue ticket](https:\u002F\u002Fgithub.com\u002Ffreqtrade\u002Ffreqtrade-strategies\u002Fissues\u002Fnew) or as a [Pull request](https:\u002F\u002Fgithub.com\u002Ffreqtrade\u002Ffreqtrade-strategies\u002Fpulls) enhancing this repository.\n\n## FAQ\n\n### What is Freqtrade?\n\n[Freqtrade](https:\u002F\u002Fgithub.com\u002Ffreqtrade\u002Ffreqtrade) Freqtrade is a free and open source crypto trading bot written in Python.\nIt 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.\n\n### What includes these strategies?\n\nEach Strategies includes:  \n\n- [x] **Minimal ROI**: Minimal ROI optimized for the strategy.\n- [x] **Stoploss**: Optimal stoploss.\n- [x] **Buy signals**: Result from Hyperopt or based on exisiting trading strategies.\n- [x] **Sell signals**: Result from Hyperopt or based on exisiting trading strategies.\n- [x] **Indicators**: Includes the indicators required to run the strategy.\n\nBest backtest multiple strategies with the exchange and pairs you're interrested in, and finetune the strategy to the markets you're trading.\n\n### How to install a strategy?\n\nFirst you need a [working Freqtrade](https:\u002F\u002Ffreqtrade.io).\n\nOnce you have the bot on the right version, follow this steps:\n\n1. Select the strategy you want. All strategies of the repo are into \n[user_data\u002Fstrategies](https:\u002F\u002Fgithub.com\u002Ffreqtrade\u002Ffreqtrade-strategies\u002Ftree\u002Fmain\u002Fuser_data\u002Fstrategies)\n2. Copy the strategy file\n3. Paste it into your `user_data\u002Fstrategies` folder\n4. Run the bot with the parameter `--strategy \u003CSTRATEGY CLASS NAME>` (ex: `freqtrade trade --strategy Strategy001`)\n\nMore information [about backtesting](https:\u002F\u002Fwww.freqtrade.io\u002Fen\u002Flatest\u002Fbacktesting\u002F) and [strategy customization](https:\u002F\u002Fwww.freqtrade.io\u002Fen\u002Flatest\u002Fstrategy-customization\u002F).\n\n### How to test a strategy?\n\nLet assume you have selected the strategy `strategy001.py`:\n\n#### Simple backtesting\n\n```bash\nfreqtrade backtesting --strategy Strategy001\n```\n\n#### Refresh your test data\n\n```bash\nfreqtrade download-data --days 100\n```\n\n*Note:* Generally, it's recommended to use static backtest data (from a defined period of time) for comparable results.\n\nPlease check out the [official backtesting documentation](https:\u002F\u002Fwww.freqtrade.io\u002Fen\u002Flatest\u002Fbacktesting\u002F) for more information.\n","该项目提供了一系列免费的交易策略，专为Freqtrade交易机器人设计。核心功能包括多种买入\u002F卖出策略，旨在帮助用户在加密货币市场中实现自动化交易。所有策略均采用Python编写，并经过回测验证，适用于Freqtrade 2022.4或更高版本。这些策略适合那些希望通过量化方法优化其交易表现的个人投资者和开发者。值得注意的是，项目强调了对策略进行充分测试的重要性，建议用户先通过回测及Dry-run模式熟悉后再实际操作。此外，具备一定的编程基础将有助于更好地理解和调整这些策略。",2,"2026-06-11 03:57:28","trending"]