Explore a Reinforcement Learning Mechanism for Trading Wind Power Futures in this NYU Brooklyn Quant Experience (BQE) Seminar Series talk by Adjunct Professor Bruno Kamdem. Delve into topics such as energy security, market setup, machine learning, and reinforcement learning models. Examine the policy contracts, historical data, and development work involved in this innovative approach to wind power trading. Gain insights into narrow predictability, expectations theorem, and the implications for energy credits in this comprehensive presentation on applying advanced quantitative techniques to renewable energy markets.
A Reinforcement Learning Mechanism for Trading Wind Power Futures
New York University (NYU) via YouTube
Overview
Syllabus
Introduction
What next
Energy security
Narrow predictability
Market setup
Machine learning
Reinforcementlearning
Models
Model
Policy
Contracts
Awap
Work of Development
Expectations
Theorem
Data
Historical Data
Discussion
Are they getting out of these credits
Taught by
NYU Tandon School of Engineering
