Optimization of Multi-Factor Model in Quantitative Trading Based On Reinforcement LearningDownload PDF

Dec 14, 2020 (edited Dec 26, 2020)CUHK 2021 Course IERG5350 Blind SubmissionReaders: Everyone
  • Keywords: Quantitative trading, Reinforcement learning, Multi-factor model
  • TL;DR: Use Reinforcement learning to construct alpha strategy in Chinese stock market
  • Abstract: Quantitative trading strategies play an important role in stock trading, and reinforcement learning (RL) has been increasingly applied to trading activities in recent years. In this paper, we mainly study the optimization of multi-factor model in quantitative trading by using the method of RL, that we train an agent with a series of historical trading data of the stock market. From the experiment results, we can see that RL is feasible in solving and optimizing similar investment decision-making problems in financial field, which can help us to obtain more stable returns.Eventually, we hope that our simple work can make more and more people notice the application of RL in investment.
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