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#### 100% online

Start instantly and learn at your own schedule.

#### Approx. 21 hours to complete

Suggested: 6 hours/week...

#### English

Subtitles: English

### Skills you will gain

option pricing and risk managementsimple model for market dynamicsQ-learning using financial problemsoptimal tradingPortfolio Optimization

#### 100% online

Start instantly and learn at your own schedule.

#### Approx. 21 hours to complete

Suggested: 6 hours/week...

#### English

Subtitles: English

### Syllabus - What you will learn from this course

Week
1
4 hours to complete

## MDP and Reinforcement Learning

14 videos (Total 107 min), 2 readings, 1 quiz
14 videos
Introduction to Markov Decision Processes and Reinforcement Learning in Finance9m
MDP and RL: Decision Policies9m
MDP & RL: Value Function and Bellman Equation7m
MDP & RL: Value Iteration and Policy Iteration4m
MDP & RL: Action Value Function9m
Options and Option pricing7m
Black-Scholes-Merton (BSM) Model8m
BSM Model and Risk9m
Discrete Time BSM Model7m
Discrete Time BSM Hedging and Pricing8m
Discrete Time BSM BS Limit6m
Jupyter Notebook FAQ10m
Hedged Monte Carlo: low variance derivative pricing with objective probabilities10m
Week
2
4 hours to complete

## MDP model for option pricing: Dynamic Programming Approach

7 videos (Total 59 min), 2 readings, 1 quiz
7 videos
Backward Recursion for Q Star8m
Basis Functions8m
Optimal Hedge With Monte-Carlo8m
Optimal Q Function With Monte-Carlo10m
Jupyter Notebook FAQ10m
QLBS: Q-Learner in the Black-Scholes(-Merton) Worlds10m
Week
3
4 hours to complete

## MDP model for option pricing - Reinforcement Learning approach

8 videos (Total 71 min), 3 readings, 1 quiz
8 videos
Q-Learning8m
Fitted Q-Iteration10m
Fitted Q-Iteration: the Ψ-basis9m
Fitted Q-Iteration at Work11m
RL Solution: Discussion and Examples11m
Jupyter Notebook FAQ10m
QLBS: Q-Learner in the Black-Scholes(-Merton) Worlds and The QLBS Learner Goes NuQLear10m
Course Project Reading: Global Portfolio Optimization10m
Week
4
5 hours to complete

## RL and INVERSE RL for Portfolio Stock Trading

10 videos (Total 82 min), 2 readings, 1 quiz
10 videos
One Period Rewards6m
Forward and Inverse Optimisation10m
Reinforcement Learning for Portfolios9m
Entropy Regularized RL8m
RL Equations10m
RL and Inverse Reinforcement Learning Solutions10m
Course Summary3m
Jupyter Notebook FAQ10m
3.3
15 Reviews

### Top reviews from Reinforcement Learning in Finance

By LCJun 6th 2019

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.

## About 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....

## About the Machine Learning and Reinforcement Learning in Finance Specialization

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....