This repository is used for managing my assignment solution as well as study materials for CME 241: Reinforcement Learning for Stochastic Control Problems in Finance, taught by Prof. Ashwin Rao at Stanford University, winter 2020.
My solution for assignments are listed and linked as follows:
| Lecture | Topic | Written Assignment | Programming Assignment |
|---|---|---|---|
| 1 | Overview | ||
| 2 | MP, MRP and MDP | Link | MP / MRP / MDP / Policy |
| 3 | Dynamic Programming | Link | Policy Evaluation / Policy Iteration / Value Iteration |
| 4 | Risk-Aversion, Utility Theory | Link | |
| 5-9 | Application Problems of RL in Finance | Merton's Portfolio problem | Optimal Asset Allocation |
| 10-11 | Model-free Prediction | Interface / Monte-Carlo / TD(0) / TD(lambda) / Comparison | |
| 12 | Model-free Control | Link | MC Control / SARSA / Q-Learning |
| 13-14 | Function Approximation | TBD | |
| 15 | Value Function Geometry, Gradient TD | ||
| 16 | Guest Lecture | ||
| 17 | Policy Gradient | Link | REINFORCE |
| 18 | Evolutionary Strategies, Integrating Learning and Planning | ||
| 19 | Exploration vs Exploitation | Link | Multi-armed Bandits |
| 20 | Special Topics |
To install all dependencies, run:
pip install -r ./assignment/requirements.txt
A list of resources (including github repo, lectures, papers, talks etc.) which I personally find useful are listed and linked here