本課程是 Machine Learning and Reinforcement Learning in Finance 專項課程專項課程的一部分

3.6
星
118 個評分

Igor Halperin

17,113 人已註冊

提供方

Machine Learning and Reinforcement Learning in Finance 專項課程New York University

課程信息

9,413 次近期查看

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.

可靈活調整截止日期

根據您的日程表重置截止日期。

可分享的證書

完成後獲得證書

100% 在線

立即開始，按照自己的計劃學習。

第 3 門課程（共 4 門）

Machine Learning and Reinforcement Learning in Finance 專項課程

高級

完成時間大約為17 小時

英語（English）

字幕：英語（English）

您將獲得的技能

option pricing and risk management
simple model for market dynamics
Q-learning using financial problems
optimal trading
Portfolio Optimization

可靈活調整截止日期

根據您的日程表重置截止日期。

可分享的證書

完成後獲得證書

100% 在線

立即開始，按照自己的計劃學習。

第 3 門課程（共 4 門）

Machine Learning and Reinforcement Learning in Finance 專項課程

高級

完成時間大約為17 小時

英語（English）

字幕：英語（English）

授課教師

授課教師評分

4/5 （8 個評分）

Igor Halperin

42,610 個學生

4 門課程

提供方

New York University

New York University is a leading global institution for scholarship, teaching, and research. Based in New York City with campuses and sites in 14 additional major cities across the world, NYU embraces diversity among faculty, staff and students to ensure the highest caliber, most inclusive educational experience.

授課大綱 - 您將從這門課程中學到什麼

週

週 1

完成時間為 4 小時

MDP and Reinforcement Learning

完成時間為 4 小時

14 個視頻（總計 107 分鐘）, 2 個閱讀材料, 1 個測驗

14 個視頻

Introduction to the Specialization4分鐘

Prerequisites7分鐘

Welcome to the Course5分鐘

Introduction to Markov Decision Processes and Reinforcement Learning in Finance9分鐘

MDP and RL: Decision Policies9分鐘

MDP & RL: Value Function and Bellman Equation7分鐘

MDP & RL: Value Iteration and Policy Iteration4分鐘

MDP & RL: Action Value Function9分鐘

Options and Option pricing7分鐘

Black-Scholes-Merton (BSM) Model8分鐘

BSM Model and Risk9分鐘

Discrete Time BSM Model7分鐘

Discrete Time BSM Hedging and Pricing8分鐘

Discrete Time BSM BS Limit6分鐘

2 個閱讀材料

Jupyter Notebook FAQ10分鐘

Hedged Monte Carlo: low variance derivative pricing with objective probabilities10分鐘

週

週 2

完成時間為 4 小時

MDP model for option pricing: Dynamic Programming Approach

完成時間為 4 小時

7 個視頻（總計 59 分鐘）, 2 個閱讀材料, 1 個測驗

週

週 3

完成時間為 4 小時

MDP model for option pricing - Reinforcement Learning approach

完成時間為 4 小時

8 個視頻（總計 71 分鐘）, 3 個閱讀材料, 1 個測驗

8 個視頻

Week Introduction2分鐘

Batch Reinforcement Learning9分鐘

Stochastic Approximations8分鐘

Q-Learning8分鐘

Fitted Q-Iteration10分鐘

Fitted Q-Iteration: the Ψ-basis9分鐘

Fitted Q-Iteration at Work11分鐘

RL Solution: Discussion and Examples11分鐘

3 個閱讀材料

Jupyter Notebook FAQ10分鐘

QLBS: Q-Learner in the Black-Scholes(-Merton) Worlds and The QLBS Learner Goes NuQLear10分鐘

Course Project Reading: Global Portfolio Optimization10分鐘

週

週 4

完成時間為 5 小時

RL and INVERSE RL for Portfolio Stock Trading

完成時間為 5 小時

10 個視頻（總計 82 分鐘）, 2 個閱讀材料, 1 個測驗

10 個視頻

Week Welcome Video2分鐘

Introduction to RL for Trading12分鐘

Portfolio Model8分鐘

One Period Rewards6分鐘

Forward and Inverse Optimisation10分鐘

Reinforcement Learning for Portfolios9分鐘

Entropy Regularized RL8分鐘

RL Equations10分鐘

RL and Inverse Reinforcement Learning Solutions10分鐘

Course Summary3分鐘

2 個閱讀材料

Jupyter Notebook FAQ10分鐘

Multi-period trading via Convex Optimization10分鐘

審閱

3.6

31 條評論

5 stars
48.30%
4 stars
15.25%
3 stars
4.23%
2 stars
10.16%
1 star
22.03%

來自REINFORCEMENT LEARNING IN FINANCE的熱門評論

由 LC 提供2019年6月5日

Excellent course. The peer reviewed evaluation is very interisting and it is definitely worth the time to do it in detail but does not take two hours with luck a week.

由 SM 提供2021年6月23日

Challenging course as a non-finance person, but learned a lot.

查看所有評論

關於 Machine Learning and Reinforcement Learning in Finance 專項課程

The main goal of this specialization is to provide the knowledge and practical skills necessary to develop a strong foundation on core paradigms and algorithms of machine learning (ML), with a particular focus on applications of ML to various practical problems in Finance.

The specialization aims at helping students to be able to solve practical ML-amenable problems that they may encounter in real life that include: (1) mapping the problem on a general landscape of available ML methods, (2) choosing particular ML approach(es) that would be most appropriate for resolving the problem, and (3) successfully implementing a solution, and assessing its performance. The specialization is designed for three categories of students: · Practitioners working at financial institutions such as banks, asset management firms or hedge funds · Individuals interested in applications of ML for personal day trading · 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. The modules can also be taken individually to improve relevant skills in a particular area of applications of ML to finance.

Machine Learning and Reinforcement Learning in Finance

常見問題

我什么时候能够访问课程视频和作业？
讲座和作业的访问权限取决于您的注册类型。如果您以旁听模式参加课程，则可以免费查看大多数课程资料。要访问评分作业并获得证书，您需要在旁听期间或之后购买证书体验。如果看不到旁听选项：
课程可能不提供旁听选项。您可以尝试免费试用，也可以申请助学金。
课程可能会改为提供'完整课程，没有证书'。通过此选项，您可以查看所有课程材料、提交所要求的作业，以及获得最终成绩。这也意味着您将无法购买证书体验。
我订阅此专项课程后会得到什么？
您注册课程后，将有权访问专项课程中的所有课程，并且会在完成课程后获得证书。您的电子课程证书将添加到您的成就页中，您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容，可以免费旁听课程。
有助学金吗？
是的。如果您负担不起学习计划的注册费，则可以在选择学习计划时申请助学金或奖学金。如果您选择的学习计划提供助学金或奖学金，则您将在描述页面上看到一个申请链接。

還有其他問題嗎？請訪問學生幫助中心。

Reinforcement Learning in Finance

課程信息

您將獲得的技能