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MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.
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.
Course 4 of 4 in the Machine Learning and Reinforcement Learning in Finance Specialization
Syllabus
WEEK 1: Black-Scholes-Merton model, Physics and Reinforcement Learning
WEEK 2: Reinforcement Learning for Optimal Trading and Market Modeling
WEEK 3: Perception - Beyond Reinforcement Learning
WEEK 4: Other Applications of Reinforcement Learning: P-2-P Lending, Cryptocurrency, etc.
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.