本课程是 Investment Management with Python and Machine Learning 专项课程专项课程的一部分

4.8
星
436 个评分

Lionel Martellini, PhD 另外 +1 位授课教师

16,918 人已注册

提供方

Investment Management with Python and Machine Learning 专项课程北方高等商学院

课程信息

18,334 次近期查看

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.

可灵活调整截止日期

根据您的日程表重置截止日期。

可分享的证书

完成后获得证书

100% 在线

立即开始，按照自己的计划学习。

第 2 门课程（共 4 门）

Investment Management with Python and Machine Learning 专项课程

中级

完成时间大约为12 小时

英语（English）

字幕：阿拉伯语（Arabic）, 法语（French）, （欧洲人讲的）葡萄牙语, 意大利语, 越南语, 德语（German）, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）

您将学到的内容有

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

可灵活调整截止日期

根据您的日程表重置截止日期。

可分享的证书

完成后获得证书

100% 在线

立即开始，按照自己的计划学习。

第 2 门课程（共 4 门）

Investment Management with Python and Machine Learning 专项课程

中级

完成时间大约为12 小时

英语（English）

授课教师

授课教师评分

4.87/5 （102 个评分）

Lionel Martellini, PhD

EDHEC-Risk Institute, Director

Finance

54,640 个学生

3 门课程

Vijay Vaidyanathan, PhD

Optimal Asset Management Inc.

CEO

51,601 个学生

2 门课程

提供方

北方高等商学院

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.

授课大纲 - 您将从这门课程中学到什么

周

周 1

完成时间为 4 小时

Style & Factors

完成时间为 4 小时

9 个视频（总计 114 分钟）, 3 个阅读材料, 1 个测验

9 个视频

Welcome video3分钟

Introduction to factor investing12分钟

Factor models and the CAPM9分钟

Multi-Factor models and Fama-French7分钟

Factor benchmarks and Style analysis8分钟

Shortcomings of cap-weighted indices11分钟

From cap-weighted benchmarks to smart-weighted benchmarks12分钟

Introduction to Lab sessions6分钟

Module 1 Lab Session - Foundations42分钟

3 个阅读材料

Requirements2分钟

Material at your disposal5分钟

Module 1- Key points2分钟

1 个练习

Module 1- Graded Quiz1小时

周

周 2

完成时间为 2 小时

Robust estimates for the covariance matrix

完成时间为 2 小时

7 个视频（总计 70 分钟）, 1 个阅读材料, 1 个测验

7 个视频

The curse of dimensionality11分钟

Estimating the Covariance Matrix with a Factor Model9分钟

Honey I Shrunk the Covariance Matrix!7分钟

Portfolio Construction with Time-Varying Risk Parameters8分钟

Exponentially weighted average8分钟

ARCH and GARCH Models9分钟

Module 2 Lab Session - Covariance Estimation13分钟

1 个阅读材料

Module 2-Key points2分钟

1 个练习

Module 2 - Graded quiz1小时

周

周 3

完成时间为 3 小时

Robust estimates for expected returns

完成时间为 3 小时

7 个视频（总计 77 分钟）, 3 个阅读材料, 1 个测验

7 个视频

Lack of Robustness of Expected Return Estimates10分钟

Agnostic Priors on Expected Return Estimates6分钟

Using Factor Models to Estimate Expected Returns11分钟

Extracting Implied Expected Returns8分钟

Introducing Active Views6分钟

Black-Litterman Analysis10分钟

Module 3 Lab Session- Black Litterman23分钟

3 个阅读材料

Module 3-Key points2分钟

The Intuition Behind Black-Litterman Model Portfolios10分钟

Importat message before the quiz!10分钟

1 个练习

Module 3 - Graded Quiz1小时

周

周 4

完成时间为 3 小时

Portfolio Optimization in Practice

完成时间为 3 小时

7 个视频（总计 67 分钟）, 4 个阅读材料, 1 个测验

7 个视频

Naive Diversification11分钟

Scientific Diversification11分钟

Measuring risk contributions6分钟

Simplified risk parity portfolios7分钟

Risk Parity Portfolios7分钟

Comparing Diversification Options8分钟

Module 4 Lab Session - Risk Contribution and Risk Parity15分钟

4 个阅读材料

Module 4-Key points2分钟

Survey: Alternative Equity Beta Investing10分钟

Dive into heuristic diversification10分钟

To be continued (2)10分钟

1 个练习

Module 4 - Graded quiz1小时

审阅

4.8

118 条评论

5 stars
81.85%
4 stars
13.15%
3 stars
3.85%
2 stars
0.68%
1 star
0.45%

来自ADVANCED PORTFOLIO CONSTRUCTION AND ANALYSIS WITH PYTHON的热门评论

由 MM 提供Dec 2, 2019

The course is excellent, one of the best finance courses on coursera, but you should know in advance that you will not have any help from the staff, at least that was my experience.

由 CC 提供Jan 31, 2021

Really a great course, instructors video then are a great resource. I'd have liked more mathematical analysis but I understand it could have gone beyond scope.

由 NN 提供Mar 6, 2020

Very interesting course with a lot practice stuff. A very proficient mentors with strong theoretical background in finance and good Python skills.

由 AC 提供Sep 26, 2020

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

查看所有评论

关于 Investment Management with Python and Machine Learning 专项课程

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.

常见问题

我什么时候能够访问课程视频和作业？
讲座和作业的访问权限取决于您的注册类型。如果您以旁听模式参加课程，则可以免费查看大多数课程资料。要访问评分作业并获得证书，您需要在旁听期间或之后购买证书体验。如果看不到旁听选项：
课程可能不提供旁听选项。您可以尝试免费试用，也可以申请助学金。
课程可能会改为提供'完整课程，没有证书'。通过此选项，您可以查看所有课程材料、提交所要求的作业，以及获得最终成绩。这也意味着您将无法购买证书体验。
我订阅此专项课程后会得到什么？
您注册课程后，将有权访问专项课程中的所有课程，并且会在完成课程后获得证书。您的电子课程证书将添加到您的成就页中，您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容，可以免费旁听课程。
有助学金吗？
是的。如果您负担不起学习计划的注册费，则可以在选择学习计划时申请助学金或奖学金。如果您选择的学习计划提供助学金或奖学金，则您将在描述页面上看到一个申请链接。

还有其他问题吗？请访问学生帮助中心。

Advanced Portfolio Construction and Analysis with Python