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.
Advanced Portfolio Construction and Analysis with Python
Advanced Portfolio Construction and Analysis with Python
This course is part of Investment Management with Python and Machine Learning Specialization
Instructors: Claudia Carrone
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4.7
(502 reviews)
Intermediate level
Some related experience required
12 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
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
Details to know
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Assessments
4 assignments
Taught in English
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This course is part of the Investment Management with Python and Machine Learning Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
What's included
9 videos3 readings1 assignment1 discussion prompt1 ungraded lab
What's included
7 videos1 reading1 assignment1 discussion prompt
What's included
7 videos3 readings1 assignment1 discussion prompt
What's included
7 videos4 readings1 assignment1 discussion prompt
Instructors
Instructor ratings
4.9 (121 ratings)Offered by
Recommended if you're interested in Finance
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Sungkyunkwan University
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Imperial College London
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4.7
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Showing 3 of 502
RP
5
Reviewed on Jul 15, 2020
Again, both instructors built on the first course, were crystal clear, and made the course enjoyable to both watch and implement the learnings.
RS
5
Reviewed on Feb 27, 2021
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)
YK
5
Reviewed on Oct 7, 2020
An in depth explanation of factor models and alternative measures of portfolio diversity, with excellent explanations of the accompanying Python notebooks.
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