hadrianl / DRLTrade

try to train the network for trade, using PPO

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DRLTrade

try to train the network for trade, using PPO, RL, LSTM

  • internal data source
  • base on 1min ohlcv data

PPO2

  • assum that we enter the market at any time and exit after 500 bar
  • we decide how much position we should hold after every minutes, 3 action is allowed. hold 1 long pos, hold 1 short pos or hold 0 pos
  • LSTM helps to figure out the trading continuity during this 500 bar
  • one hand we use actor to make the decision , the other hand we use critic to adjust the params
  • final goal is to maximize the pnl after 500 bar
  • profit in the future should be considered less attractive, just like the cash flow discount
  • commision need to be set, but no slippage

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try to train the network for trade, using PPO


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Language:Python 100.0%