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

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Vijay Vaidyanathan, PhD +1 more instructor

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Offered By

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. This course provides an introduction to the underlying science, with the aim of giving you a thorough understanding of that scientific basis. However, 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. 
This course is the first in a four course specialization in Data Science and Machine Learning in Asset Management but can be taken independently. In this course, we cover the basics of Investment Science, and we'll build practical implementations of each of the concepts along the way. We'll start with the very basics of risk and return and quickly progress to cover a range of topics including several Nobel Prize winning concepts. We'll cover some of the most popular practical techniques in modern, state of the art investment management and portfolio construction. 

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.

Flexible deadlines

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Shareable Certificate

Earn a Certificate upon completion

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Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 1 of 4 in the

Investment Management with Python and Machine Learning Specialization

Approx. 25 hours to complete

English

What you will learn

Gain an intuitive understanding for the underlying theory behind Modern Portfolio Construction Techniques
Write custom Python code to estimate risk and return parameters
Utilize powerful Python optimization libraries to build scientifically and systematically diversified portfolios
Build custom utilities in Python to test and compare portfolio strategies

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.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 1 of 4 in the

Investment Management with Python and Machine Learning Specialization

Approx. 25 hours to complete

English

Instructors

Instructor rating

4.87/5 (443 Ratings)

Vijay Vaidyanathan, PhD

Optimal Asset Management Inc.

CEO

58,074 Learners

2 Courses

Lionel Martellini, PhD

EDHEC-Risk Institute, Director

Finance

61,342 Learners

3 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

Content Rating94%(4,161 ratings)

Week1

Week 1

7 hours to complete

Analysing returns

7 hours to complete

14 videos (Total 225 min), 6 readings, 1 quiz

14 videos

Welcome video3mInstalling Anaconda3mFundamentals of Returns10mLab Session-Basics of returns29mMeasures of Risk and Reward9mLab Session-Risk Adjusted returns28mMeasuring Max Drawdown10mLab Session-Drawdown30mDeviations from Normality9mLab Session-Building your own modules12mDownside risk measures8mLab Session-Deviations from Normality30mEstimating VaR10mLab Session-Semi Deviation, VAR and CVAR27m

6 readings

Material at your disposal5mMaterial for the Lab Sessions10mModule 1- Key points2mINCORRECT STATEMENT IN “DEVIATION FROM NORMALITY” VIDEO10mSemi Deviation10mBefore the Quiz10m

1 practice exercise

Module 1 Graded Quiz1h

Week2

Week 2

4 hours to complete

An Introduction to Portfolio Optimization

4 hours to complete

10 videos (Total 172 min), 1 reading, 1 quiz

10 videos

The only free lunch in Finance11mLab Session-Efficient frontier-Part 123mMarkowitz Optimization and the Efficient Frontier9mApplying quadprog to draw the efficient Frontier11mLab Session-Asset Efficient Frontier-Part 220mLab Session-Applying Quadprog to Draw the Efficient Frontier38mFund Separation Theorem and the Capital Market Line7mLab Session-Locating the Max Sharpe Ratio Portfolio25mLack of robustness of Markowitz analysis5mLab Session-Plotting EW and GMV on the Efficient Frontier20m

1 reading

Module 2 - Key points2m

1 practice exercise

Module 2 Graded Quiz1h

Week3

Week 3

5 hours to complete

Beyond Diversification

5 hours to complete

15 videos (Total 236 min), 4 readings, 1 quiz

15 videos

Limits of diversification8mLab session- Limits of Diversification-Part119mLab session-Limits of diversification-Part 222mAn introduction to CPPI - Part 17mAn introduction to CPPI - Part 210mLab session-CPPI and Drawdown Constraints-Part129mLab session-CPPI and Drawdown Constraints-Part228mSimulating asset returns with random walks10mMonte Carlo Simulation6mLab Session-Random Walks and Monte Carlo22mAnalyzing CPPI strategies11mLab Session-Installing IPYWIDGETS5mDesigning and calibrating CPPI strategies12mLab session - interactive plots of monte Carlo Simulations of CPPI and GBM-Part119mLab session - interactive plots of monte Carlo Simulations of CPPI and GBM-Part221m

4 readings

Module 3 - Key points2mipywidgets installation - info5mgbm function10mInstruction prior to begin the module 3 graded quizz10m

1 practice exercise

Module 3 Graded Quiz45m

Week4

Week 4

9 hours to complete

Introduction to Asset-Liability Management

9 hours to complete

12 videos (Total 327 min), 5 readings, 1 quiz

12 videos

From Asset Management to Asset-Liability Management7mLab Session-Present Values,liabilities and funding ratio22mLiability hedging portfolios12mLab Session-CIR Model and cash vs ZC bonds1h 8mLiability-driven investing (LDI)10mLab Session-Liability driven investing51mChoosing the policy portfolio14mLab Session-Monte Carlo simulation of coupon-bearing bonds using CIR33mBeyond LDI11mLab Session-Naive risk budgeting between the PSP & GHP44mLiability-friendly equity portfolios10mLab Session-Dynamic risk budgeting between PSP & LHP40m

5 readings

Module 4 - Key points2mDynamic Liability-Driven Investing Strategies: The Emergence Of A New Investment Paradigm For Pension Funds?1h 30mLiability-Driven-Investing1hInstruction prior to begin module 4 graded quiz2mTo be continued (1)5m

1 practice exercise

Module 4 Graded Quiz1h

Reviews

4.8

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TOP REVIEWS FROM INTRODUCTION TO PORTFOLIO CONSTRUCTION AND ANALYSIS WITH PYTHON

by MANov 29, 2020

Awesome Course, Great instructors that give a nice balance of theory and practice, the practice is very hands-on and will help you understand the theory and give you useful tools from the first week.

by JJJun 10, 2021

Well taught and really like the mix between practical and theoretical lectures. Explain in simple language and starts off simple but gets progressively harder. Highly recommended.

by MBJun 19, 2020

Seriously an amazing course! I have got great learning of both financial concepts and python coding. instructors are super amazing. The approach is quite practical and useful.

by DHMay 26, 2020

Enjoyable course. One has to be conversant with basic Phyton to follow this course. What I learnt the most is the ability to use Phyton coding to demonstrate the concept of portfolio investment.

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.

Introduction to Portfolio Construction and Analysis with Python

About this Course

What you will learn