本課程是 Investment Management with Python and Machine Learning 專項課程專項課程的一部分

John Mulvey - Princeton University 另外 +1 位授課教師

提供方

Investment Management with Python and Machine Learning 專項課程北方高等商学院

課程信息

30,404 次近期查看

This course will enable you mastering machine-learning approaches in the area of investment management. It has been designed by two thought leaders in their field, Lionel Martellini from EDHEC-Risk Institute and John Mulvey from Princeton University. Starting from the basics, they will help you build practical skills to understand data science so you can make the best portfolio decisions.
The course will start with an introduction to the fundamentals of machine learning, followed by an in-depth discussion of the application of these techniques to portfolio management decisions, including the design of more robust factor models, the construction of portfolios with improved diversification benefits, and the implementation of more efficient risk management models. 

We have designed a 3-step learning process: first, we will introduce a meaningful investment problem and see how this problem can be addressed using statistical techniques. Then, we will see how this new insight from Machine learning can complete and improve the relevance of the analysis.

You will have the opportunity to capitalize on videos and recommended readings to level up your financial expertise, and to use the quizzes and Jupiter notebooks to ensure grasp of concept.

At the end of this course, you will master the various machine learning techniques in investment management.

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第 3 門課程（共 4 門）

Investment Management with Python and Machine Learning 專項課程

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中級

完成時間大約為15 小時

英語（English）

字幕：英語（English）

您將學到的內容有

Learn the principles of supervised and unsupervised machine learning techniques to financial data sets

Understand the basis of logistical regression and ML algorithms for classifying variables into one of two outcomes

Utilize powerful Python libraries to implement machine learning algorithms in case studies

Learn about factor models and regime switching models and their use in investment management

您將獲得的技能

Programming skillsManaging your own personal invetsmentsInvestment management knowledgeComputer ScienceExpertise in data science

可分享的證書

完成後獲得證書

100% 在線

立即開始，按照自己的計劃學習。

第 3 門課程（共 4 門）

Investment Management with Python and Machine Learning 專項課程

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

完成時間大約為15 小時

英語（English）

字幕：英語（English）

講師

授課教師評分

2.94/5 （19 個評分）

John Mulvey - Princeton University

Professor in the Operations Research and Financial Engineering Department and a founding member of the Bendheim Centre for Finance at Princeton University

Finance

8,324 個學生

1 門課程

Lionel Martellini, PhD

EDHEC-Risk Institute, Director

Finance

28,906 個學生

3 門課程

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.

教學大綱 - 您將從這門課程中學到什麼

週

週 1

完成時間為 2 小時

Introducing the fundamentals of machine learning

完成時間為 2 小時

8 個視頻（總計 59 分鐘）, 4 個閱讀材料, 1 個測驗

8 個視頻

Welcome to the Python Machine-Learning for Investment Management course4分鐘

Introduction to machine-learning7分鐘

Financial applications7分鐘

Supervised learning7分鐘

First algorithms7分鐘

Highlights of best practice6分鐘

Unsupervised learning7分鐘

Challenges ahead10分鐘

4 個閱讀材料

Requirements2分鐘

Material at your disposal2分鐘

Machine Learning for Investment Decisions: A Brief Guided Tour10分鐘

References for module 1"Introducing the fundamentals of machine learning"10分鐘

1 個練習

Module 1Graded Quiz30分鐘

週

週 2

完成時間為 4 小時

Machine learning techniques for robust estimation of factor models

完成時間為 4 小時

8 個視頻（總計 80 分鐘）, 2 個閱讀材料, 1 個測驗

8 個視頻

Introduction to module 2 - Basics of factor investing8分鐘

Introducing Factor Models7分鐘

Typology of factor models9分鐘

Using factor models in portfolio construction and analysis10分鐘

Penalty methods9分鐘

Setting factor loadings and examples7分鐘

Shrinkage concepts7分鐘

Lab session - Jupiter notebook on Factor Models20分鐘

2 個閱讀材料

References for module 2"Machine learning techniques for robust estimation of factor models"10分鐘

Information on Jupyter notebook - Factor models10分鐘

1 個練習

Module 2 Graded Quiz1小時

週

週 3

完成時間為 3 小時

Machine learning techniques for efficient portfolio diversification

完成時間為 3 小時

8 個視頻（總計 88 分鐘）, 2 個閱讀材料, 1 個測驗

8 個視頻

Introduction to module 3 -Machine learning techniques for efficient portfolio diversification7分鐘

Benefits of portfolio diversification8分鐘

Portfolio diversification measures12分鐘

Principle component analysis8分鐘

Role of clustering6分鐘

Graphical analysis8分鐘

Selecting a portfolio of assets7分鐘

Graphical Network Analysis28分鐘

2 個閱讀材料

References for the module "Machine learning techniques for efficient portfolio diversification"10分鐘

Reference for the module "Selecting a portfolio of assets"10分鐘

1 個練習

Module 3 Graded Quiz45分鐘

週

週 4

完成時間為 3 小時

Machine learning techniques for regime analysis

完成時間為 3 小時

7 個視頻（總計 65 分鐘）, 4 個閱讀材料, 1 個測驗

7 個視頻

Introduction to economic regimes7分鐘

Portfolio Decisions with Time-Varying Market Conditions10分鐘

Trend filtering6分鐘

A scenario based portfolio model8分鐘

A two regime portfolio example7分鐘

A multi regime model for a University Endowment9分鐘

Lab session- Jupyter notebook on regime-based investment model15分鐘

4 個閱讀材料

Information on the "trend filtering" video2分鐘

Information on "scenario based portfolio model" video2分鐘

References for the module "Machine learning techniques for regime analysis"10分鐘

Information on Jupyter notebookon regime-based investment model10分鐘

1 個練習

Module 4 Graded Quiz1小時

關於 Investment Management with Python and Machine Learning 專項課程

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.

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Python and Machine Learning for Asset Management