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Reinforcement Learning in Finance(으)로 돌아가기

New York University의 Reinforcement Learning in Finance 학습자 리뷰 및 피드백

114개의 평가
30개의 리뷰

강좌 소개

This course aims at introducing the fundamental concepts of Reinforcement Learning (RL), and develop use cases for applications of RL for option valuation, trading, and asset management. By the end of this course, students will be able to - Use reinforcement learning to solve classical problems of Finance such as portfolio optimization, optimal trading, and option pricing and risk management. - Practice on valuable examples such as famous Q-learning using financial problems. - Apply their knowledge acquired in the course to a simple model for market dynamics that is obtained using reinforcement learning as the course project. Prerequisites are the courses "Guided Tour of Machine Learning in Finance" and "Fundamentals of Machine Learning in Finance". Students are expected to know the lognormal process and how it can be simulated. Knowledge of option pricing is not assumed but desirable....

최상위 리뷰

필터링 기준:

Reinforcement Learning in Finance의 28개 리뷰 중 26~28

교육 기관: 秦源

2021년 1월 10일

the simulation method may not work well in reality. If use other methods like deep-q-learning, it will be much better

교육 기관: Charl M

2020년 11월 23일

There is too much focus on quantitative financial analysis, and not enough time on explaining RL. Simple financial examples are beneficial to understand the practical use of RL in finance, but I felt that this course had a strong bias towards finance. I feel I still need to do further reading in order to apply RL in my work. The assignment did not supply all the data required to perform the tasks. The peer grading process did not work, we had to rely on sharing links in the discussion section to get our assignments graded.

교육 기관: 吕子赳

2021년 8월 25일

T​he accent of the professor is completely a disaster !!!! Never try this course unless you are confident that you can learn every thing just by reading matrials of this course. Believe me