About this Course
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다음 전문 분야의 4개 강좌 중 3번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 14시간 필요

권장: 5 weeks - 2/3 hours per week...

영어

자막: 영어

배울 내용

  • Check

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

  • Check

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

  • Check

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

  • Check

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

귀하가 습득할 기술

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

다음 전문 분야의 4개 강좌 중 3번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 14시간 필요

권장: 5 weeks - 2/3 hours per week...

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 2시간 필요

Introducing the fundamentals of machine learning

8개 동영상 (총 59분), 4 readings, 1 quiz
8개의 동영상
Introduction to machine-learning7m
Financial applications7m
Supervised learning7m
First algorithms7m
Highlights of best practice6m
Unsupervised learning7m
Challenges ahead10m
4개의 읽기 자료
Requirements2m
Material at your disposal2m
Machine Learning for Investment Decisions: A Brief Guided Tour10m
References for module 1"Introducing the fundamentals of machine learning"10m
1개 연습문제
Module 1Graded Quizz30m
2
완료하는 데 4시간 필요

Machine learning techniques for robust estimation of factor models

8개 동영상 (총 80분), 2 readings, 1 quiz
8개의 동영상
Introducing Factor Models7m
Typology of factor models9m
Using factor models in portfolio construction and analysis10m
Penalty methods9m
Setting factor loadings and examples7m
Shrinkage concepts7m
Lab session - Jupiter notebook on Factor Models20m
2개의 읽기 자료
References for module 2"Machine learning techniques for robust estimation of factor models"10m
Information on Jupyter notebook - Factor models10m
1개 연습문제
Module 2 Graded Quizz1h
3
완료하는 데 2시간 필요

Machine learning techniques for efficient portfolio diversification

7개 동영상 (총 59분), 1 reading, 1 quiz
7개의 동영상
Benefits of portfolio diversification8m
Portfolio diversification measures12m
Principle component analysis8m
Role of clustering6m
Graphical analysis8m
Selecting a portfolio of assets7m
1개의 읽기 자료
References for the module "Machine learning techniques for efficient portfolio diversification"10m
1개 연습문제
Module 3 Graded Quizz45m
4
완료하는 데 3시간 필요

Machine learning techniques for regime analysis

7개 동영상 (총 65분), 4 readings, 1 quiz
7개의 동영상
Portfolio Decisions with Time-Varying Market Conditions10m
Trend filtering6m
A scenario based portfolio model8m
A two regime portfolio example7m
A multi regime model for a University Endowment9m
Lab session- Jupyter notebook on regime-based investment model15m
4개의 읽기 자료
Information on the "trend filtering" video2m
Information on "scenario based portfolio model" video2m
References for the module "Machine learning techniques for regime analysis"10m
Information on Jupyter notebookon regime-based investment model10m
1개 연습문제
Module 4 Graded Quizz1h

강사

Avatar

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
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Lionel Martellini, PhD

EDHEC-Risk Institute, Director
Finance

EDHEC Business School 정보

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. ...

Investment Management with Python and Machine Learning 전문 분야 정보

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

자주 묻는 질문

  • 강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.

  • 강좌를 등록하면 전문 분야의 모든 강좌에 접근할 수 있고 강좌를 완료하면 수료증을 취득할 수 있습니다. 전자 수료증이 성취도 페이지에 추가되며 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 내용만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.

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