關於此課程：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. 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.
此課程適用人群：The course is designed for three categories of students: Practitioners working at financial institutions such as banks, asset management firms or hedge funds Current full-time students pursuing a degree in Finance, Statistics, Computer Science, Mathematics, Physics, Engineering or other related disciplines who want to learn about practical applications of ML in Finance Experience with Python (including numpy, pandas, and IPython/Jupyter notebooks), linear algebra, basic probability theory and basic calculus is necessary to complete assignments in this course. In addition, students are expected to know the lognormal process and how it can be simulated. Knowledge of option pricing is not assumed but desirable.
製作方： New York University Tandon School of Engineering
教學方： Igor Halperin
| 基本信息 | |
| 級別 | 高級設置 |
| 語言 | English |
| 如何通過 | 通過所有計分作業以完成課程。 |
| 用戶評分 |
授課大綱
第 1 週
MDP and Reinforcement Learning
14 個視頻, 2 個閱讀材料
- 視頻: Prerequisites
- 視頻: Welcome to the Course
- 視頻: Introduction to Markov Decision Processes and Reinforcement Learning in Finance
- 視頻: MDP and RL: Decision Policies
- 視頻: MDP & RL: Value Function and Bellman Equation
- 視頻: MDP & RL: Value Iteration and Policy Iteration
- 視頻: MDP & RL: Action Value Function
- 視頻: Options and Option pricing
- 視頻: Black-Scholes-Merton (BSM) Model
- 視頻: BSM Model and Risk
- 視頻: Discrete Time BSM Model
- 視頻: Discrete Time BSM Hedging and Pricing
- 視頻: Discrete Time BSM BS Limit
- Leyendo: Jupyter Notebook FAQ
- Libreta: Discrete-time Black Scholes model
- Leyendo: Hedged Monte Carlo: low variance derivative pricing with objective probabilities
已評分: Discrete-time Black Scholes model
第 2 週
MDP model for option pricing: Dynamic Programming Approach
7 個視頻, 2 個閱讀材料
- 視頻: Action-Value Function
- 視頻: Optimal Action From Q Function
- 視頻: Backward Recursion for Q Star
- 視頻: Basis Functions
- 視頻: Optimal Hedge With Monte-Carlo
- 視頻: Optimal Q Function With Monte-Carlo
- Leyendo: Jupyter Notebook FAQ
- Libreta: QLBS Model Implementation
- Leyendo: QLBS: Q-Learner in the Black-Scholes(-Merton) Worlds
已評分: QLBS Model Implementation
第 3 週
MDP model for option pricing - Reinforcement Learning approach
8 個視頻, 3 個閱讀材料
- 視頻: Batch Reinforcement Learning
- 視頻: Stochastic Approximations
- 視頻: Q-Learning
- 視頻: Fitted Q-Iteration
- 視頻: Fitted Q-Iteration: the Ψ-basis
- 視頻: Fitted Q-Iteration at Work
- 視頻: RL Solution: Discussion and Examples
- Leyendo: Jupyter Notebook FAQ
- Libreta: Fitted Q-Iteration
- Leyendo: QLBS: Q-Learner in the Black-Scholes(-Merton) Worlds and The QLBS Learner Goes NuQLear
- Leyendo: Course Project Reading: Global Portfolio Optimization
已評分: Fitted Q-Iteration
第 4 週
RL and INVERSE RL for Portfolio Stock Trading
10 個視頻, 2 個閱讀材料
- 視頻: Introduction to RL for Trading
- 視頻: Portfolio Model
- 視頻: One Period Rewards
- 視頻: Forward and Inverse Optimisation
- 視頻: Reinforcement Learning for Portfolios
- 視頻: Entropy Regularized RL
- 視頻: RL Equations
- 視頻: RL and Inverse Reinforcement Learning Solutions
- 視頻: Course Summary
- Leyendo: Jupyter Notebook FAQ
- Libreta: IRL Market Model Calibration
- Leyendo: Multi-period trading via Convex Optimization
已評分: IRL Market Model Calibration
常見問題解答
運作方式
Trabajo del curso
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Certificados
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製作方
New York University Tandon School of Engineering
Tandon offers comprehensive courses in engineering, applied science and technology. Each course is rooted in a tradition of invention and entrepreneurship.
價格
| 購買課程 | |
|---|---|
| 訪問課程材料 | 可用 |
| 訪問評分的材料 | 可用 |
| 收到最終成績 | 可用 |
| 獲得可共享的課程證書 | 可用 |
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