Igor Halperin
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. Tandon offers comprehensive courses in engineering, applied science and technology. Each course is rooted in a tradition of invention and entrepreneurship.
Instructor Details
Courses : 2
Specification: Overview of Advanced Methods of Reinforcement Learning in Finance
|
9 reviews for Overview of Advanced Methods of Reinforcement Learning in Finance
Add a review
| Price | Free |
|---|---|
| Provider | |
| Duration | 14 hours |
| Year | 2018 |
| Level | Expert |
| Language | English |
| Certificate | Yes |
| Quizzes | Yes |
FREE
Matthieu B –
No real follow up by the team, and the assignments have nothing to do with the classes.
Niklas O –
Interesting deep dive into a RL application in Finance at forefront of research, however be prepared for challenging project assignments with limited support or guidance. Not for the fainthearted.
Teemu P –
Assessments are once again out of touch with the materials that have been presented and do not reflect any practical uses you may need to work on in the industry. Skip this certificate until fixed.
Rodrigo A d S –
Excellent course!!!
Luis A A C –
Great course.
Ishrit T –
It was very difficult to get the peer graded assignments graded.
Daria –
Great refreshment on Stochastic calculus and overall rewind of the specialization!
Abdelrahman T A –
Thanks
Wi K –
Contents of Week1 and Week4 are really useful, as the instructor recommended several academic papers on relevant topics. However the instructor failed to expand them, at least will be helpful to outline the basic ideas of each paper. The instructor only mentioned the authors’ names and paper title. It’s a pity. However, week 2 and week 3 are totally useless in understanding finance and reinforcement learning. It’s just a pile of formulas from physics, not interesting or pertinent to course topic at all. Moreover there is a strange signal term in the drift of stochastic process. I don’t think anyone in industry is ever using this less known dynamic to pricing or trading. It’s definitely better that Week2 and Week3 could be removed completely and be replaced by expansions of the academic papers that the instructor recommended.