Reinforcement Learning

Student: Rodichkin Mikhail

Supervisor: Maria Veretennikova

Educational Programme: Statistical Modelling and Actuarial Science (Master)

Year of Graduation: 2018

Algorithmic trading showed a significant increase in interest, given the rapidly growing capabilities of modern computers. Because of the decrease in delays in trading and the increase in the productivity of machinery, high-frequency trading has become available not only to large financial firms, but also to ordinary people. This forces you to come up with more clever algorithms, because one speed is not enough for a successful trade. In this paper, a new training approach with reinforcement to the study of algorithmic trade is considered. Training methods with reinforcement are aimed at optimizing the work of the agent in an unknown environment. The considered direction is actively developing in everyday life, the most modern ones are introduced and improved.

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