Overview of Advanced Methods of Reinforcement Learning in Finance (Coursera)

Overview of Advanced Methods of Reinforcement Learning in Finance (Coursera)
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Overview of Advanced Methods of Reinforcement Learning in Finance (Coursera)
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.

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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.



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32.00 EUR/month

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