Berlin Machine Learning Seminar - Examples of Reinforcement Learning Applications in the Financial Market

October 22, 2020, Posted by Heuna Kim

I have given this talk on 22nd October 2020 at 19:00 to Berlin Machine Learning Seminar with the following abstract.

Abstract:

Reinforcement Learning has been broadly employed in financial markets for the last few years by benefiting from its nature of combining the behavior optimization (in this case buy and sell) and the market prediction. We will first discuss the hierarchical reinforcement learning scheme deployed by JPMorgan (arXiv, NIPS Workshop 2018) and then take a look at other two examples of DRL applied in trading. The first one (arXiv, KDD 2019) is implementing an interpretable network that works similar to a traditional trading strategy (Buying-Winners-and-Selling-Losers). The second one (arXiv, ICML 2019) is extending a traditional mathematical model (the Almgren and Chriss model) to a multi-agent setting in order to optimize a liquidation strategy.

The slides: here

Please contact me if you have any followup questions.

You can find my other technical talks in the github repo hahey/Talks.