This course is part of the Investment Management with Python and Machine Learning Specialization

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Lionel Martellini, PhD +1 more instructor

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Investment Management with Python and Machine Learning SpecializationEDHEC Business School

About this Course

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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.
As we cover the theory and math in lecture videos, we'll also implement the concepts in Python, and you'll be able to code along with us so that you have a deep and practical understanding of how those methods work. By the time you are done, not only will you have a foundational understanding of modern computational methods in investment management, you'll have practical mastery in the implementation of those methods. If you follow along and implement all the lab exercises, you will complete the course with a powerful toolkit that you will be able to use to perform your own analysis and build your own implementations and perhaps even use your newly acquired knowledge to improve on current methods.

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Course 2 of 4 in the

Investment Management with Python and Machine Learning Specialization

Intermediate Level

Approx. 12 hours to complete

English

What you will 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

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 2 of 4 in the

Investment Management with Python and Machine Learning Specialization

Intermediate Level

Approx. 12 hours to complete

English

Instructors

Instructor rating

4.87/5 (107 Ratings)

Lionel Martellini, PhD

EDHEC-Risk Institute, Director

Finance

61,402 Learners

3 Courses

Vijay Vaidyanathan, PhD

Optimal Asset Management Inc.

CEO

58,131 Learners

2 Courses

Offered by

EDHEC Business School

Founded in 1906, EDHEC is now one of Europe’s top 15 business schools .

Based in Lille, Nice, Paris, London and Singapore, and counting over 90 nationalities on its campuses, EDHEC is a fully international school directly connected to the business world. With over 40,000 graduates in 120 countries, it trains committed managers capable of dealing with the challenges of a fast-evolving world. Harnessing its core values of excellence, innovation and entrepreneurial spirit, EDHEC has developed a strategic model founded on research of true practical use to society, businesses and students, and which is particularly evident in the work of EDHEC-Risk Institute and Scientific Beta. The School functions as a genuine laboratory of ideas and plays a pioneering role in the field of digital education via EDHEC Online, the first fully online degree-level training platform. These various components make EDHEC a centre of knowledge, experience and diversity, geared to preparing new generations of managers to excel in a world subject to transformational change. EDHEC in figures: 8,600 students in academic education, 19 degree programmes ranging from bachelor to PhD level, 184 professors and researchers, 11 specialist research centres.

Syllabus - What you will learn from this course

Week1

Week 1

4 hours to complete

Style & Factors

4 hours to complete

9 videos (Total 114 min), 3 readings, 1 quiz

9 videos

Welcome video3mIntroduction to factor investing12mFactor models and the CAPM9mMulti-Factor models and Fama-French7mFactor benchmarks and Style analysis8mShortcomings of cap-weighted indices11mFrom cap-weighted benchmarks to smart-weighted benchmarks12mIntroduction to Lab sessions6mModule 1 Lab Session - Foundations42m

3 readings

Requirements2mMaterial at your disposal5mModule 1- Key points2m

1 practice exercise

Module 1- Graded Quiz1h

Week2

Week 2

2 hours to complete

Robust estimates for the covariance matrix

2 hours to complete

7 videos (Total 70 min), 1 reading, 1 quiz

Week3

Week 3

3 hours to complete

Robust estimates for expected returns

3 hours to complete

7 videos (Total 77 min), 3 readings, 1 quiz

7 videos

Lack of Robustness of Expected Return Estimates10mAgnostic Priors on Expected Return Estimates6mUsing Factor Models to Estimate Expected Returns11mExtracting Implied Expected Returns8mIntroducing Active Views6mBlack-Litterman Analysis10mModule 3 Lab Session- Black Litterman23m

3 readings

Module 3-Key points2mThe Intuition Behind Black-Litterman Model Portfolios10mImportat message before the quiz!10m

1 practice exercise

Module 3 - Graded Quiz1h

Week4

Week 4

3 hours to complete

Portfolio Optimization in Practice

3 hours to complete

7 videos (Total 67 min), 4 readings, 1 quiz

7 videos

Naive Diversification11mScientific Diversification11mMeasuring risk contributions6mSimplified risk parity portfolios7mRisk Parity Portfolios7mComparing Diversification Options8mModule 4 Lab Session - Risk Contribution and Risk Parity15m

4 readings

Module 4-Key points2mSurvey: Alternative Equity Beta Investing10mDive into heuristic diversification10mTo be continued (2)10m

1 practice exercise

Module 4 - Graded quiz1h

Reviews

4.8

120 reviews

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TOP REVIEWS FROM ADVANCED PORTFOLIO CONSTRUCTION AND ANALYSIS WITH PYTHON

by MMApr 13, 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.

by LLSep 4, 2021

This course gives a good understanding of Fama-French, GARCH, Black-Litterman and risk parity models among many others, not only theoretically, but also through hands-on Lab sessions.

by KAJan 4, 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.

by PRJun 29, 2020

Fantastic portfolio construction techniques, although black letterman model could have been explained better . Overall great course with real world financial applications

View all reviews

About the Investment Management with Python and Machine Learning Specialization

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.

Frequently Asked Questions

When will I have access to the lectures and assignments?
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.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

Advanced Portfolio Construction and Analysis with Python

About this Course

What you will learn