Overview of Advanced Methods of Reinforcement Learning in Finance
Discover the advanced methods of Reinforcement Learning in Finance. Learn about option pricing, market impact modeling, and price dynamics. Explore the applications of Reinforcement Learning in high-frequency trading, cryptocurrencies, and peer-to-peer lending.
In the last course of our specialization, Overview of Advanced Methods of Reinforcement Learning in Finance, we will take a deeper look into topics discussed in our third course, Reinforcement Learning in Finance.
In particular, we will talk about links between Reinforcement Learning, option pricing and physics, implications of Inverse Reinforcement Learning for modeling market impact and price dynamics, and perception-action cycles in Reinforcement Learning. Finally, we will overview trending and potential applications of Reinforcement Learning for high-frequency trading, cryptocurrencies, peer-to-peer lending, and more.
After taking this course, students will be able to
– explain fundamental concepts of finance such as market equilibrium, no arbitrage, predictability,
– discuss market modeling,
– Apply the methods of Reinforcement Learning to high-frequency trading, credit risk peer-to-peer lending, and cryptocurrencies trading.
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