Recurrent Reinforcement Learning Implementation using Matlab/Octave

20210321 Update: A PyTorch-port of this repo is available at ceshine/RRL_PyTorch.

Reference: Stock Trading with Recurrent Reinforcement Learning (RRL) By Gabriel Molina

File Description

Core Functions

costFunction.m
updateFt.m
rewardFunction.m
featureNormalize.m
sharpRatio.m

Utility Functions

checkRRLGradient.m : Verify the correctness of gradient function in cost function
getNumericalGradient.m : Approximate gradient (inefficiently) for verification

Test Function:

testTWSE.m : Use Taiwan Weighted Stock Index from Taiwan Stock Exchange.
testDAX.m : Use DAX index of Germany.