Overview of Advanced Methods of Reinforcement Learning in Finance
This course is part of Machine Learning and Reinforcement Learning in Finance Specialization
Instructor: Igor Halperin
Skills you'll gain
There are 4 modules in this course
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.
Reinforcement Learning for Optimal Trading and Market Modeling
Perception - Beyond Reinforcement Learning
Other Applications of Reinforcement Learning: P-2-P Lending, Cryptocurrency, etc.
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