The practice of investment management has been transformed in recent years by computational methods. Instead of merely explaining the science, we help you build on that foundation in a practical manner, with an emphasis on the hands-on implementation of those ideas in the Python programming language. In this course, we cover the estimation, of risk and return parameters for meaningful portfolio decisions, and also introduce a variety of state-of-the-art portfolio construction techniques that have proven popular in investment management and portfolio construction due to their enhanced robustness.
Programa Especializado - Investment Management with Python and Machine LearningEscuela de Negocios EDHECAcerca de este Curso
55,345 vistas recientes
Certificado para compartir
Obtén un certificado al finalizar
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 intermedio
Aprox. 11 horas para completar
Inglés (English)
Subtítulos: Inglés (English)
Qué aprenderás
Analyze style and factor exposures of portfolios
Implement robust estimates for the covariance matrix
Implement Black-Litterman portfolio construction analysis
Implement a variety of robust portfolio construction models
Certificado para compartir
Obtén un certificado al finalizar
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 intermedio
Aprox. 11 horas para completar
Inglés (English)
Subtítulos: Inglés (English)
ofrecido por
Escuela de Negocios EDHEC
Founded in 1906, EDHEC is now one of Europe’s top 15 business schools .
Programa - Qué aprenderás en este curso
3 horas para completar
Style & Factors
3 horas para completar
9 videos (Total 114 minutos), 3 lecturas, 1 cuestionario
9 videos
Introduction to factor investing12m
Factor models and the CAPM9m
Multi-Factor models and Fama-French7m
Factor benchmarks and Style analysis8m
Shortcomings of cap-weighted indices11m
From cap-weighted benchmarks to smart-weighted benchmarks12m
Introduction to Lab sessions6m
Module 1 Lab Session - Foundations42m
3 lecturas
Requirements2m
Material at your disposal5m
Module 1- Key points2m
1 ejercicio de práctica
Module 1- Graded Quiz1h
2 horas para completar
Robust estimates for the covariance matrix
2 horas para completar
7 videos (Total 70 minutos), 1 lectura, 1 cuestionario
7 videos
Estimating the Covariance Matrix with a Factor Model9m
Honey I Shrunk the Covariance Matrix!7m
Portfolio Construction with Time-Varying Risk Parameters8m
Exponentially weighted average8m
ARCH and GARCH Models9m
Module 2 Lab Session - Covariance Estimation13m
1 lectura
Module 2-Key points2m
1 ejercicio de práctica
Module 2 - Graded quiz1h
3 horas para completar
Robust estimates for expected returns
3 horas para completar
7 videos (Total 77 minutos), 2 lecturas, 1 cuestionario
7 videos
Agnostic Priors on Expected Return Estimates6m
Using Factor Models to Estimate Expected Returns11m
Extracting Implied Expected Returns8m
Introducing Active Views6m
Black-Litterman Analysis10m
Module 3 Lab Session- Black Litterman23m
2 lecturas
Module 3-Key points2m
The Intuition Behind Black-Litterman Model Portfolios10m
1 ejercicio de práctica
Module 3 - Graded Quiz1h
3 horas para completar
Portfolio Optimization in Practice
3 horas para completar
7 videos (Total 67 minutos), 4 lecturas, 1 cuestionario
7 videos
Scientific Diversification11m
Measuring risk contributions6m
Simplified risk parity portfolios7m
Risk Parity Portfolios7m
Comparing Diversification Options8m
Module 4 Lab Session - Risk Contribution and Risk Parity15m
4 lecturas
Module 4-Key points2m
Survey: Alternative Equity Beta Investing10m
Dive into heuristic diversification10m
To be continued (2)10m
1 ejercicio de práctica
Module 4 - Graded quiz1h
Revisiones
Principales revisiones sobre ADVANCED PORTFOLIO CONSTRUCTION AND ANALYSIS WITH PYTHON
por MM13 de abr. de 2020
Loved how this course was presented. It built well off of the first course and provided labs that let me explore the content. I really enjoyed how Lionel and Vijay presented the material.
por KA4 de ene. de 2020
I like the way instructors explained difficult topic and digest it to simple way. The coding side was also impressive. WIth novice background in Python, I would able to understand.
por DB4 de may. de 2020
This course teaches a great approach to portfolio construction. Crisp course content makes learning even more convenient. My sincere regards to the team behind this noble task,
por MG11 de abr. de 2020
Really appreciated from both of the instructors, from thier very high level of theory and practical programming skills. Hoping to use these khowledge in pracsis some days.
Acerca de Programa especializado: Investment Management with Python and Machine Learning
The Data Science and Machine Learning for Asset Management Specialization has been designed to deliver a broad and comprehensive introduction to modern methods in Investment Management, with a particular emphasis on the use of data science and machine learning techniques to improve investment decisions.By the end of this specialization, you will have acquired the tools required for making sound investment decisions, with an emphasis not only on the foundational theory and underlying concepts, but also on practical applications and implementation. Instead of merely explaining the science, we help you build on that foundation in a practical manner, with an emphasis on the hands-on implementation of those ideas in the Python programming language through a series of dedicated lab sessions.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
- The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
- The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
¿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?
Si estás suscrito, obtienes una prueba gratis de 7 días, que podrás cancelar cuando desees sin ningún tipo de penalidad. Una vez transcurrido ese tiempo, no realizamos reembolsos. No obstante, puedes cancelar tu suscripción cuando quieras. Consulta nuestra política completa de reembolsos.
¿Hay ayuda económica disponible?
Sí, Coursera ofrece ayuda económica a los estudiantes que no pueden pagar la tarifa. Solicítala haciendo clic en el enlace de Ayuda económica que está debajo del botón “Inscribirse” a la izquierda. Se te pedirá que completes una solicitud. Recibirás una notificación en caso de que se apruebe. Deberás completar este paso para cada uno de los cursos que forman parte del Programa especializado, incluido el proyecto final. Obtén más información.
¿Tienes más preguntas? Visita el Centro de Ayuda al Alumno.
