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返回到 Advanced Portfolio Construction and Analysis with Python

学生对 北方高等商学院 提供的 Advanced Portfolio Construction and Analysis with Python 的评价和反馈

437 个评分


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....



Apr 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.


Feb 17, 2021

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.


101 - Advanced Portfolio Construction and Analysis with Python 的 118 个评论(共 118 个)

创建者 Aditya G

May 24, 2020

This course was useful in understanding the details of constructing portfolios in terms of covariance and expected returns estimates. I think this course compared to the first part of the specialization is more relevant to institutional investors rather than individuals

创建者 Drew I

Apr 17, 2020

I liked that the quizzes required a greater understanding of Python, however I wish the instructor moved slower through the labs; I also would have appreciated more labs to hammer home an understanding of more of the taught concepts. Overall good course!

创建者 劉映麟

Jan 26, 2020

The course is great, the professor will walk you through different asset allocation models and provide the python code of the model. The code part is quite useful, but when it comes to quizzes, the instruction is not that clear and sometimes wrong.

创建者 Laszlo B

May 3, 2022

T​he first course contained much more relevant code to the theory, but basically it is very informative and I know this leds to a higher purpose (next courses). I like the style of the instructors.

创建者 Cindy X

Aug 2, 2021

very good quality, covers very in depth knowledge in portfolio construction, but I find the python part is a bit challenging unless you have good command of python programming.

创建者 Miguel A L C

Sep 3, 2020

The concepts are easy to understand, the teachers explain very well, at the end you have more tools to improve the generation of portfilios construction.

创建者 Alfredo H

Apr 26, 2020

Very good in depth course extension from the first, however, would appreciate more applications and deeper applications of introduced investing ideas

创建者 Tobias T

Aug 31, 2020

Great and interesting course like MOOC 1, but it would be great if the code would be explained a bit more in detail like in the first MOOC.

创建者 Alejandro C

Sep 27, 2020

Sometimes the material covering the python code is insufficient. Maybe provide additional learning resources just for the python portion.

创建者 Hector B

Jan 25, 2021

Good theory and practical exercises. The presented code can be a little confusing depending on your previous frameworks you have used.

创建者 Loi H H

Jul 29, 2022

Learnt a lot about portfolio construction and python!

创建者 Francisco V A

Jun 29, 2020

I loved the first module of this specialization. I think it does a great job setting up the foundations for portfolio analysis and I gave it 5 stars. I actually decided to complete the certification after the first module.

I still intend to complete the specialization, but I didn't like this module as much. I think the lab sessions are too shallow. "Play around" doesn't really cut it as instruction. There's a big gap between the lab sessions and the exams that are actually quite large for non-programmers. I would really like Vijay to spend more time playing around with the data rather than letting us figure stuff out on our own.

Overall my feedback is that this is a good course for programmers trying to become financial analysts but not so much for financial analysts trying to hone their technical skills.

I would have given 4 stars had it not been for the quiz of Week 3. Students will see the forum, because it's just impossible to pass. I strongly recommend EDHEC to revamp the entire Week 3 training.

创建者 Maximiliano M

Nov 30, 2021

T​he course in general is good, specially in python programming. The only. problem is that some models where explained in a light mode (to avoid saying poorly): Black-litterman and factor models portfolio constructions were not explained with the same detail as they did with other models previously explained. The same is valid for smart beta strategies. Hope this is taken into account to improve the course experience.

创建者 赵晨昊

Sep 4, 2021

Need more lab sessions!!!

创建者 Julien d M d B

Jul 4, 2020

The course are really great but the lab session are really not clear, leading to quiz confusing and giving the feeling that we are completely lost

创建者 Sara C

Oct 30, 2021

Python labs are SUPER rushed, bit of an anti climax after the first course!!

创建者 Luke M

Dec 26, 2020

Quite a few mistakes in the course content.

创建者 Pongsak T

Feb 14, 2021

awful, not recommend