课程信息
23,888 次近期查看

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

中级

完成时间大约为19 小时

建议:4 weeks, from 3 to 4 hours per week...

英语(English)

字幕:英语(English)

您将学到的内容有

  • Check

    Analyze style and factor exposures of portfolios

  • Check

    Implement robust estimates for the covariance matrix

  • Check

    Implement Black-Litterman portfolio construction analysis

  • Check

    Implement a variety of robust portfolio construction models

100% 在线

立即开始,按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

中级

完成时间大约为19 小时

建议:4 weeks, from 3 to 4 hours per week...

英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1
完成时间为 3 小时

Style & Factors

9 个视频 (总计 114 分钟), 3 个阅读材料, 1 个测验
9 个视频
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
2
完成时间为 2 小时

Robust estimates for the covariance matrix

7 个视频 (总计 70 分钟), 1 个阅读材料, 1 个测验
7 个视频
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
3
完成时间为 3 小时

Robust estimates for expected returns

7 个视频 (总计 77 分钟), 2 个阅读材料, 1 个测验
7 个视频
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
2 个阅读材料
Module 3-Key points2分钟
The Intuition Behind Black-Litterman Model Portfolios10分钟
1 个练习
Module 3 - Graded Quiz1小时
4
完成时间为 3 小时

Portfolio Optimization in Practice

7 个视频 (总计 67 分钟), 4 个阅读材料, 1 个测验
7 个视频
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
4.7
5 条评论Chevron Right

来自Advanced Portfolio Construction and Analysis with Python的热门评论

创建者 MMDec 3rd 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.

创建者 KRNov 6th 2019

Very demanding, especially the tests. Extremely interesting lectures and to the point.

讲师

Avatar

Lionel Martellini, PhD

EDHEC-Risk Institute, Director
Finance
Avatar

Vijay Vaidyanathan, PhD

Optimal Asset Management Inc.
CEO

关于 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. ...

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....
Investment Management with Python and Machine Learning

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