Об этом курсе: In the last course of our specialization, Overview of Advanced Methods of Reinforcement Learning in Finance, we will take a deeper look into topics discussed in our third course, Reinforcement Learning in Finance. In particular, we will talk about links between Reinforcement Learning, option pricing and physics, implications of Inverse Reinforcement Learning for modeling market impact and price dynamics, and perception-action cycles in Reinforcement Learning. Finally, we will overview trending and potential applications of Reinforcement Learning for high frequency trading, cryptocurrencies, peer-to-peer lending, and more.
Для кого этот курс: 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 A pre-requisite to this course is the course “Reinforcement Learning in Finance”. Familiarity with main financial models such as Markowitz portfolio model, capital asset pricing model (CAPM) and the Black-Scholes model is desirable not not neccessary.
Автор: New York University Tandon School of Engineering
Преподаватели: Igor Halperin
| Основные сведения | |
| Уровень | Продвинутые функции |
| Язык | English |
| Как пройти курс | Чтобы пройти курс, выполните все оцениваемые задания. |
Программа курса
НЕДЕЛЯ 1
Black-Scholes-Merton model, Physics and Reinforcement Learning
13 видео
- Видео: Specialization Prerequisites
- Видео: Interview with Rossen Roussev
- Видео: Reinforcement Learning and Ptolemy's Epicycles
- Видео: PDEs in Physics and Finance
- Видео: Competitive Market Equilibrium Models in Finance
- Видео: I Certainly Hope You Are Wrong, Herr Professor!
- Видео: Risk as a Science of Fluctuation
- Видео: Markets and the Heat Death of the Universe
- Видео: Option Trading and RL
- Видео: Liquidity
- Видео: Modeling Market Frictions
- Видео: Modeling Feedback Frictions
Оцениваемый: Assignment 1
НЕДЕЛЯ 2
Reinforcement Learning for Optimal Trading and Market Modeling
8 видео
- Видео: Invisible Hand
- Видео: GBM and Its Problems
- Видео: The GBM Model: An Unbounded Growth Without Defaults
- Видео: Dynamics with Saturation: The Verhulst Model
- Видео: The Singularity is Near
- Видео: What are Defaults?
- Видео: Quantum Equilibrium-Disequilibrium
Оцениваемый: Assignment 2
НЕДЕЛЯ 3
Perception - Beyond Reinforcement Learning
8 видео
- Видео: Market Dynamics and IRL
- Видео: Diffusion in a Potential: The Langevin Equation
- Видео: Classical Dynamics
- Видео: Potential Minima and Newton's Law
- Видео: Classical Dynamics: the Lagrangian and the Hamiltonian
- Видео: Langevin Equation and Fokker-Planck Equations
- Видео: The Fokker-Planck Equation and Quantum Mechanics
Оцениваемый: Assignment 3
НЕДЕЛЯ 4
Other Applications of Reinforcement Learning: P-2-P Lending, Cryptocurrency, etc.
9 видео
- Видео: Electronic Markets and LOB
- Видео: Trades, Quotes and Order Flow
- Видео: Limit Order Book
- Видео: LOB Modeling
- Видео: LOB Statistical Modeling
- Видео: LOB Modeling with ML and RL
- Видео: Other Applications of RL
- Видео: The Value of Universatility
- Notebook: Final Project: Exploration of non-linear market model dynamics
Оцениваемый: Final Project
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Авторы
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.
Стоимость
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