DDPG based on multi-scale strokes for financial time series trading strategy. (arXiv:2207.10071v1 [q-fin.TR])

With the development of artificial intelligence,more and more financial
practitioners apply deep reinforcement learning to financial trading
strategies.However,It is difficult to extract accurate features due to the
characteristics of considerable noise,highly non-stationary,and non-linearity
of single-scale time series,which makes it hard to obtain high returns.In this
paper,we extract a multi-scale feature matrix on multiple time scales of
financial time series,according to the classic financial theory-Chan Theory,and
put forward to an approach of multi-scale stroke deep deterministic policy
gradient reinforcement learning model(MSSDDPG)to …

arxiv ddpg financial scale series strategy time time series trading