Overview of Advanced Methods of Reinforcement Learning in Finance
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...
By Igor Halperin on Coursera
About This Course
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.
Topics Covered
Frequently Asked Questions
How much does Overview of Advanced Methods of Reinforcement Learning in Finance cost?
Visit the Overview of Advanced Methods of Reinforcement Learning in Finance course page for current pricing and available discounts.
Who teaches Overview of Advanced Methods of Reinforcement Learning in Finance?
Overview of Advanced Methods of Reinforcement Learning in Finance is taught by Igor Halperin, New York University.
What skill level is Overview of Advanced Methods of Reinforcement Learning in Finance for?
This course is designed for advanced learners.
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