Updated May 21, 2018
This is the open source do-it-yourself version of Gekko.
Gekko is free and 100% open source, you download and run the software on your own machine. Gekko only talks to the exchanges (if you want it too). We don’t know anyhing about your strategies, usage, portfolio size or anything else (unless you tell us).
Gekko supports 25 different exchanges (including Bitfinex, Bitstamp and Poloniex). Just tell Gekko which exchange you want to interact with and Gekko talks directly to the exchange.
Gekko makes it possible to create your own trading strategies using TA indicators. Once you created it you can use Gekko to backtest your strategy over historical market data or run against the live market (using either a paper trader or real trader – making it a trading bot).
Using plugins Gekko is able to update you wherever you are! Plugins are available for IRC, telegram, email and a lot of other platforms. Without effort you are able to add your own plugins to Gekko.
Gekko runs flawlessly on all major operating systems (Windows, Linux, macOS), you can run it in the cloud or on your raspberry PI without any problems!
Gekko can watch the realtime markets. You can apply automated trading methods to realtime data coming in to do live or simulated trading (automated trading or paper trading). Gekko also stores the market data it sees so you can run the trading methods with simulate trades on a set of historical data to see whether they would have been profitable during that time (backtesting).
Gekko, as well as the current bitcoin exchanges, are not built for HFT or anything related to being the fastest. The trading methods Gekko can do are based on indicators used by human day traders. The result is that Gekko does not look at data below the one minute timescale and (depending on configuration) and will normally not trade more than a couple of times per week (also depending on configuration).
Configuring Gekko consists of three parts:
Watching a realtime market
Automate trading advice
Gekko will take care of:
Aggregating live market data
Executing live orders (tradebot)
Simulating order execution (paper trader)
Calculating profit and risk metrics
Graphing the results in a web interface
Managing and importing historical market data
Simulating live markets using historical data (backtesting)
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