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배울 내용

  • 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

공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 4개 강좌 중 2번째 강좌:
유동적 마감일
일정에 따라 마감일을 재설정합니다.
중급 단계
완료하는 데 약 11시간 필요
영어
자막: 영어

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강의 계획 - 이 강좌에서 배울 내용

1

1

완료하는 데 3시간 필요

Style & Factors

완료하는 데 3시간 필요
9개 동영상 (총 114분), 3 개의 읽기 자료, 1 개의 테스트
9개의 동영상
Introduction to factor investing12m
Factor models and the CAPM9m
Multi-Factor models and Fama-French7m
Factor benchmarks and Style analysis8m
Shortcomings of cap-weighted indices11m
From cap-weighted benchmarks to smart-weighted benchmarks12m
Introduction to Lab sessions6m
Module 1 Lab Session - Foundations42m
3개의 읽기 자료
Requirements2m
Material at your disposal5m
Module 1- Key points2m
1개 연습문제
Module 1- Graded Quiz1시간
2

2

완료하는 데 2시간 필요

Robust estimates for the covariance matrix

완료하는 데 2시간 필요
7개 동영상 (총 70분), 1 개의 읽기 자료, 1 개의 테스트
7개의 동영상
Estimating the Covariance Matrix with a Factor Model9m
Honey I Shrunk the Covariance Matrix!7m
Portfolio Construction with Time-Varying Risk Parameters8m
Exponentially weighted average8m
ARCH and GARCH Models9m
Module 2 Lab Session - Covariance Estimation13m
1개의 읽기 자료
Module 2-Key points2m
1개 연습문제
Module 2 - Graded quiz1시간
3

3

완료하는 데 3시간 필요

Robust estimates for expected returns

완료하는 데 3시간 필요
7개 동영상 (총 77분), 2 개의 읽기 자료, 1 개의 테스트
7개의 동영상
Agnostic Priors on Expected Return Estimates6m
Using Factor Models to Estimate Expected Returns11m
Extracting Implied Expected Returns8m
Introducing Active Views6m
Black-Litterman Analysis10m
Module 3 Lab Session- Black Litterman23m
2개의 읽기 자료
Module 3-Key points2m
The Intuition Behind Black-Litterman Model Portfolios10m
1개 연습문제
Module 3 - Graded Quiz1시간
4

4

완료하는 데 3시간 필요

Portfolio Optimization in Practice

완료하는 데 3시간 필요
7개 동영상 (총 67분), 4 개의 읽기 자료, 1 개의 테스트
7개의 동영상
Scientific Diversification11m
Measuring risk contributions6m
Simplified risk parity portfolios7m
Risk Parity Portfolios7m
Comparing Diversification Options8m
Module 4 Lab Session - Risk Contribution and Risk Parity15m
4개의 읽기 자료
Module 4-Key points2m
Survey: Alternative Equity Beta Investing10m
Dive into heuristic diversification10m
To be continued (2)10m
1개 연습문제
Module 4 - Graded quiz1시간

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ADVANCED PORTFOLIO CONSTRUCTION AND ANALYSIS WITH PYTHON의 최상위 리뷰

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Investment Management with Python and Machine Learning 특화 과정 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

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