TradingGym
Unverified ML strategy on Multi by Yvictor. BotFinder score 18 out of 100.
Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.
Source: github
BotFinder analysis pending.
TradingGym
TradingGym TradingGym is a toolkit for training and backtesting the reinforcement learning algorithms. This was inspired by OpenAI Gym and imitated the framework form. Not only traning env but also has backtesting and in the future will implement realtime trading env with Interactivate Broker API and so on. This training env originally design for tickdata, but also support for ohlc data format. WIP. Installation Getting Started - obsdatalen: observation data length - steplen: when call step rolling windows will + steplen - df exmaple |index|datetime|bid|ask|price|volume|serialnumber|dealin| |-----|--------|---|---|-----|------|-------------|------| |0|2010-05-25 08:45:00|7188.0|7188.0|7188.0|527.0|0.0|0.0| |1|2010-05-25 08:45:00|7188.0|7189.0|7189.0|1.0|1.0|1.0| |2|2010-05-25 08:45:00|7188.0|7189.0|7188.0|1.0|2.0|-1.0| |3|2010-05-25 08:45:00|7188.0|7189.0|7188.0|4.0|3.0|-1.0| |4|2010-05-25 08:45:00|7188.0|7189.0|7188.0|2.0|4.0|-1.0| - df: dataframe that contain data for trading serialnumber -> serial num of deal at each day recalculating - fee: when each deal will pay the fee, set wi
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