66 lines
4.2 KiB
Markdown
66 lines
4.2 KiB
Markdown
# Freqtrade
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[](https://travis-ci.org/freqtrade/freqtrade)
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[](https://coveralls.io/github/freqtrade/freqtrade?branch=develop)
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[](https://codeclimate.com/github/freqtrade/freqtrade/maintainability)
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<a class="github-button" href="https://github.com/freqtrade/freqtrade" data-icon="octicon-star" data-size="large" aria-label="Star freqtrade/freqtrade on GitHub">Star</a>
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<a class="github-button" href="https://github.com/freqtrade/freqtrade/fork" data-icon="octicon-repo-forked" data-size="large" aria-label="Fork freqtrade/freqtrade on GitHub">Fork</a>
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<a class="github-button" href="https://github.com/freqtrade/freqtrade/archive/master.zip" data-icon="octicon-cloud-download" data-size="large" aria-label="Download freqtrade/freqtrade on GitHub">Download</a>
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<a class="github-button" href="https://github.com/freqtrade" data-size="large" aria-label="Follow @freqtrade on GitHub">Follow @freqtrade</a>
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## Introduction
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Freqtrade is a crypto-currency algorithmic trading software develop in python (3.6+) supported on windows, macOs and Linux.
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!!! Danger "DISCLAIMER"
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This software is 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.
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Always start by running a trading bot in Dry-run and do not engage money before you understand how it works and what profit/loss you should expect.
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We strongly recommend you to have basic coding skills and Python knowledge. Do not hesitate to read the source code and understand the mechanisms of this bot, algorithms and techniques implemented in it.
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## Features
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1. Download market data: Download historical data of the exchange and the markets your may want to trade with.
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2. Select markets: Create your list or use an automatic one based on top traded volume (not available during backtesting). You can blacklist markets you don't want to trade.
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3. Backtest: Test your strategy on past data (based on [ohlcv](https://en.wikipedia.org/wiki/Open-high-low-close_chart) candles).
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4. Optimize: Find the best parameters for your strategy using machining learning. You can optimize buy, sell, take profit (ROI) and stop-loss.
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5. Run: Run the bot on exchange with simulated money (dry-run) or with real money (live).
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6. Run using edge (optional module): The concept is to find the best historical [trade expectancy](https://www.freqtrade.io/en/latest/edge/#expectancy) by markets based on variation of the stop-loss and then allow/reject markets to trade (the sizing of the trade is based on a risk of a percentage of your capital).
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7. Control/Monitor/Analyse: Use Telegram or a REST API (start/stop the bot, profit/loss, daily summary, current open trades results...). Futher analysis can be done as trades are saved (SQLite database).
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## Requirements
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### Up to date clock
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The clock on the system running the bot must be accurate, synchronized to a NTP server frequently enough to avoid problems with communication to the exchanges.
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### Hardware requirements
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To run this bot we recommend you a cloud instance with a minimum of:
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- 2GB RAM
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- 1GB disk space
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- 2vCPU
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### Software requirements
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- Python 3.6.x
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- pip (pip3)
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- git
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- TA-Lib
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- virtualenv (Recommended)
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- Docker (Recommended)
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## Support
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Help / Slack
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For any questions not covered by the documentation or for further information about the bot, we encourage you to join our Slack channel.
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Click [here](https://join.slack.com/t/highfrequencybot/shared_invite/enQtNjU5ODcwNjI1MDU3LTU1MTgxMjkzNmYxNWE1MDEzYzQ3YmU4N2MwZjUyNjJjODRkMDVkNjg4YTAyZGYzYzlhOTZiMTE4ZjQ4YzM0OGE) to join Slack channel.
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## Ready to try?
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Begin by reading our installation guide [here](installation).
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