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Avis et commentaires pour d'étudiants pour Introduction to Portfolio Construction and Analysis with Python par EDHEC Business School

655 évaluations
192 avis

À propos du cours

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....

Meilleurs avis


Aug 06, 2020

I am self taught in Python and have an industry background in Finance. This course was a good connector/provided additional insight on using Python to process portfolio performance and data analysis.


May 27, 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.

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1 - 25 sur 191 Avis pour Introduction to Portfolio Construction and Analysis with Python

par Benny P

Nov 27, 2019

Coming from programming background and being less theoretical, I have mixed review about this course. This course is taught by two instructors. The theory, taught by prof Lionel, is not really clear for me. The math has gone too far and too deep and overall they made things more complicated than they should. I often had to resolve to external sources to understand what the topic being discussed. The lab sessions, taught by Vijay, on the other hand is very enjoyable to follow. It's clear and clarifies the topic being taught. Vijay is not just some financial engineer that can code Python. He's very good at it. Even I with 5+ Python coding years have learnt many new tricks from his videos. Coming to the week four however, things went downhill fast. The theory is too abstract, while the videos are just too long! I think we have two or more videos with around 1 hour duration, and this is just too much.

par Leo L

Dec 12, 2019

This is one of the best online courses which combines the knowledge of Finance and Python. In fact, with python as a tool, I can have a better understanding of the theory behind it.

par Lyle D

Oct 26, 2019

Currently half-way through the course. I am really enjoying it. I am learning a lot about portfolio management and python, which is the best of both worlds for me.

The professors are excellent. Dr Vaidyanathan's lectures and labs ensure that the student learns the material and his love of the subject is infectious.

par Xinhao

Mar 08, 2020

One of the most hardcore, challenging but knowledge-harvesting courses that I ever had.

Highly recommend, and you will be better off if you type in all codes VJ did simultaneously.

par Zee

Jan 26, 2020

This is an excellent course on employing Python to make asset allocation decisions. The concepts are well-explained and the pace is quite brisk. A student can really benefit by following and redoing the Python code themselves.

For that, I would highly recommend going through the excellent Numpy, Pandas tutorials on the Enthought youtube channel, before the first week. Secondly, the course expects an understanding of Asset Allocation concepts, and it will be prudent to read up on 'Modern Portfolio Theory: Efficient and Optimal Portfolios' before the second week.

I admit that I cannot write the sophisticated code for last modules (Dr. Vijay Vaidyanathan made it look as effortless as reading a newspaper), but the course has given me the confidence that I can do that after coming up to speed on Python.

That is also my suggestion for improving the course that maybe some of the more sophisticated techniques be pushed out to later modules while building up python and asset allocation knowledge in the first module.

After finishing the course, it's quite satisfying to examine the mutual fund results, and understand how they were generated or how target date funds work or what's the logic behind the 60/40 asset allocation portfolio.

par Hong M

May 11, 2020

Thank you instructors for the fantastic teaching with profound financial principles and advanced Python techniques to make our learnings and programs applicable to present market analysis. Although it is very challenging to make all programs work well when Python version upgrade/changes, it is worthwhile to learn new things, improve Python coding skills and strengthen finance investment skills. Honored and blessed to learn a lot from this course and also from the forums of friendly classmates. Would recommend surely! Best Regards and Blessings.

par Asif R

Jan 04, 2020

Very Useful course to have a hands-on understanding of how to apply Finance concepts in investments through Python. Lectures are provided in a very succinct manner and the lab sessions are fluidly constructed. Plenty of useful python codes will get compiled in edhec_risk_kit for future use.

par Alexandre M

Nov 25, 2019

Very useful course. Both teachers are good to transmit their knowledge at a decent pace. the balance between theoretical courses and labv sessions is perfect.

par Viktor R

Jan 17, 2020

Loved it, one of the best courses I have ever taken. Only wished I had more time to spend on it, limits of what you will learn are mostly upon yourself.

par Javier M

Nov 17, 2019

Great course will continue with the rest of the courses


Jun 12, 2020

Although the course was very good, helpful and very informative but the codes were not updated which caused a lot of confusion and dissatisfaction. The codes which were not updated caused a lot of errors which were a bit frustrating at times. Also there was a bit delay in the response from the staff in clarifying the doubts and queries.

Overall it was a very good and knowledgeable experience wIth professional faculties.

Thanks and regards,


par Jerry H

Apr 29, 2020

Really enjoyed this course and found it extremely useful, from a couple of perspectives. First, the alternative perspective of managing your portfolio to meet future goals / liabilities as opposed to just return seeking was helpful, and secondly providing the construct of dynamic allocation between a performance seeking portfolio and the liability/goal hedging portfolio to be very useful. I particularly enjoyed the lab sessions that where very helpful in developed a basic understanding of the algorithms to build the code to implement the concepts in practice in my own portfolio. And as a secondary benefit, as someone who enjoys coding, I really benefited from seeing the approach to coding an application and learned a few neat tricks / capabilities along the way. I came away with a new appreciation for python and indeed Jupyter Notebooks / Lab, as I must admit I had fallen into the R camp. Look forward to taking the remaining courses.

par Sidhant M

Apr 19, 2020

One of the best online courses I've taken. It is the first I've actually completed in a while. I would mention a special word of appreciation for Dr. Vijay, his Python Lab sessions are probably the best way to learn to program for a beginner. In just a 4 week module, the amount of content covered is immense considering the course starts with the assumption that the viewer has zero knowledge in the language.

This course is the gold standard by which I will benchmark other courses. The learning I've gained from this course is beyond my wildest expectations. I'm only curious to know there's so much more this field has to offer!

par Fabien N

Jan 21, 2020

This course is one of the best course I ever took on Coursera (I have completed about 20) !!! If not the best ! The lectures are clear and the lab sessions are very helpful to understand concepts and use them by digging into the implementation. And Python notions are given along the way, which makes you feel that you are following a finance class and at the same time learning new Python features smoothly ! The last week of the course was slightly less clear and thus little bit harder, but I totally recommend this course !

par vijay c

Jul 17, 2020

very good introductory course to learn how python is used to implement portfolio strategies. coding is taught in a simple enough way to pick up and try to real-world data as well....

par Aditya G

May 05, 2020

The course was very informative and added a lot of learning and the instructors made navigating the whole syllabus very simple, even for a novice programmer and finance student

par Serg D

Nov 19, 2019

This was a great course, really good materials, great exercises, no unreasonable tasks. Great introduction into Python in finance. One thing I would say that this course is not for beginners. Prior Python knowledge will be highly beneficial. The reason why I am giving 4 is due to the lack of support in forums.

par Eduardo d M R

Nov 18, 2019

Risk Kit code needs revision from instructors! Also, it would be nice to have some feedback regarding the graded quizzes and a bit more presence on the forum. Overall, a very nice course to be introduced into Portfolio Management: would recommend with caution, nonetheless.

par Sylvain H

Aug 22, 2020

Excellent course with great pedagogy that will introduce you to individual or institutional investment management (understanding Markowitz efficient frontier and main target in portfolio construction, basic strategies for portfolio construction combining risky high-return and low-risk-return portfolios to meet liabilities, simple random walk modelling for examining virtual scenarios, and also using some real-world data), using theoretical courses as well as coding videos (notebooks are provided to play around) and quizzes using these notebooks.

Python using Pandas & some tricks.

I had almost no basic knowledge in investment and some experience with pandas, with some solid mathematical background though not an expert, and the level was perfect for me.

Watched in 1.5 ;)

par carlos j u

Sep 06, 2020

Great course!

The structure is of (1): compact, rigurous and intuitive explanations of theoretical concepts, and (2) extensive lab sessions where proffessinal Python code is developed on JupyterLab (and explained on-the-fly) that implements the concepts explained in the "lectures". Often extending them.

Emphasis is made in understanding well-written code, not in developing the math behind. The student gradually builds up their own Python module so that the code can be reused many times along the course, where needed. Moreover, the ipywidgets library is explained and used to facilitate the understanding, through interactive visualizations, of the parameters involved in many simulations.

par Kai C

Feb 09, 2020

Both two instructors are really good, patient, detail-oriented, and knowledgeable. This course is quite useful for you to gain skills in Python and its associated popular packages such as Numpy, Pandas, and Seaborn. Portfolio strategies such as CPPI and LDI are quite important and are introduced fully here. The course however takes a bit long time to finish, if you really want to make the most of it, because you must follow the long-hours labs. But I think it is worthy to spend such great amount of time.

par Chan C M

Jun 27, 2020

I like the layout of this course and the way VJ laying out his mistakes. Really help a lot for my programming and I am no longer afraid of errors. I also like how the instructor taught about liability-driven investing and how they combine the theory with the lab sessions.

One suggestion is that the course materials can be designed to teach students how they can come up with the functions. I perfectly understand how the function works but I could never come up with the functions myself.

par Ye A M

Aug 23, 2020

I have taken quite a number of Python courses(for the field of Finance) and none of the previous courses greatly improved my understanding of Python. This course, however, leaves me with nothing but a desire to dive deeper into the beauty of Python and Finance. A million thanks to both instructors for making this learning process enjoyable and interesting. 5 stars for today, for tomorrow, for as long as this course illuminates a clearer path for aspiring financial analysts!

par Runar A Ø

Dec 12, 2019

This course is very well presented and gives the reader the necessary practical skills. After short theoretical videos, most of the time is spent implementing the models in Python, and gradually building a module of functions used for constructing portfolios and visualising the data. Some of the Python code is not completely elementary so I would advice you to spend a bit more time and code everything yourself line by line and understand what's going on.


May 01, 2020

Very useful course with state of the art financial theories as well as programming practical use. I learned a lot both in finance (especially Chapter 3 & 4) and in Python in an easy and agreable way. I will be implementing a CCPI strategy in my personal portfolio soon thanks to the very useful edhec risk kit developed during all the session labs. This format is well made and makes it really fun to try and test the code for ourselves, which is rare!