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.
이 강좌는 Investment Management with Python and Machine Learning 특화 과정의 일부입니다.
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이 강좌에 대하여
배울 내용
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
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EDHEC 경영대학원
Founded in 1906, EDHEC is now one of Europe’s top 15 business schools .
강의 계획표 - 이 강좌에서 배울 내용
Style & Factors
Robust estimates for the covariance matrix
Robust estimates for expected returns
Portfolio Optimization in Practice
검토
- 5 stars81.77%
- 4 stars13.21%
- 3 stars3.87%
- 2 stars0.68%
- 1 star0.45%
ADVANCED PORTFOLIO CONSTRUCTION AND ANALYSIS WITH PYTHON의 최상위 리뷰
Good overview on portfolio theory with some of the latest trends (multi-factor models) and Python Lab sessions follow the same logic than the first course, with good tips and good timing.
Great course, nice balance between the theory (which is well explained) and the practical (python jupyter notebooks where you need to explore to gain a good understanding)
Sometimes the material covering the python code is insufficient. Maybe provide additional learning resources just for the python portion.
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,
Investment Management with Python and Machine Learning 특화 과정 정보
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.

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