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.
Este curso forma parte de Programa Especializado - Machine Learning and Reinforcement Learning in Finance
Overview of Advanced Methods of Reinforcement Learning in Finance
ofrecido por
Programa Especializado - Machine Learning and Reinforcement Learning in FinanceNew York University Tandon School of Engineering
Acerca de este Curso
10,615 vistas recientes
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Nivel avanzado
Aprox. 14 horas para completar
Sugerido: 5 hours/week
Inglés (English)
Subtítulos: Inglés (English)
Programa - Qué aprenderás en este curso
4 horas para completar
Black-Scholes-Merton model, Physics and Reinforcement Learning
4 horas para completar
13 videos (Total 103 minutos)
13 videos
Specialization Prerequisites7m
Interview with Rossen Roussev14m
Reinforcement Learning and Ptolemy's Epicycles5m
PDEs in Physics and Finance5m
Competitive Market Equilibrium Models in Finance5m
I Certainly Hope You Are Wrong, Herr Professor!7m
Risk as a Science of Fluctuation3m
Markets and the Heat Death of the Universe3m
Option Trading and RL14m
Liquidity9m
Modeling Market Frictions9m
Modeling Feedback Frictions10m
1 ejercicio de práctica
Assignment 12h
3 horas para completar
Reinforcement Learning for Optimal Trading and Market Modeling
3 horas para completar
8 videos (Total 73 minutos)
8 videos
Invisible Hand5m
GBM and Its Problems9m
The GBM Model: An Unbounded Growth Without Defaults9m
Dynamics with Saturation: The Verhulst Model7m
The Singularity is Near9m
What are Defaults?11m
Quantum Equilibrium-Disequilibrium11m
1 ejercicio de práctica
Assignment 22h
3 horas para completar
Perception - Beyond Reinforcement Learning
3 horas para completar
8 videos (Total 60 minutos)
8 videos
Market Dynamics and IRL5m
Diffusion in a Potential: The Langevin Equation8m
Classical Dynamics7m
Potential Minima and Newton's Law4m
Classical Dynamics: the Lagrangian and the Hamiltonian7m
Langevin Equation and Fokker-Planck Equations9m
The Fokker-Planck Equation and Quantum Mechanics12m
1 ejercicio de práctica
Assignment 32h
4 horas para completar
Other Applications of Reinforcement Learning: P-2-P Lending, Cryptocurrency, etc.
4 horas para completar
9 videos (Total 79 minutos)
9 videos
Electronic Markets and LOB9m
Trades, Quotes and Order Flow7m
Limit Order Book8m
LOB Modeling8m
LOB Statistical Modeling10m
LOB Modeling with ML and RL9m
Other Applications of RL7m
The Value of Universatility15m
Principales revisiones sobre Overview of Advanced Methods of Reinforcement Learning in Finance
Great refreshment on Stochastic calculus and overall rewind of the specialization!
Acerca de 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.
Acerca de Programa especializado Machine Learning and Reinforcement Learning in Finance
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.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.
¿Qué recibiré si me suscribo a este Programa especializado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
¿Cuál es la política de reembolsos?
¿Hay ayuda económica disponible?
¿Tienes más preguntas? Visita el Centro de Ayuda al Alumno.