Quantitative Asset Management - Building Systematic Real-World Strategies | Michael Robbins
Excess ReturnsSeptember 22, 202300:58:25

Quantitative Asset Management - Building Systematic Real-World Strategies | Michael Robbins

In this episode, we take a deep dive into quantitative investing with Michael Robbins, author of the new book "Quantitative Asset Management: Factor Investing and Machine Learning for Institutional Investing." We discuss data science and machine learning, factor investing, risk management, the qualities of a good back test and a lot more.

00:00 - Intro
01:58 - Why Michael wrote the book
04:11 - Is it better if the math or the finance comes first?
07:13 - What is data science?
10:39 - The best use of quantitative strategies
11:33 - The long-term impact of machine learning on investing
16:25 - Stacking premia and the equity risk premium
20:24 - The criteria Michael would use to evaluate a quantitative manager
25:09 - What makes a good investing factor?
30:13 - Does factor timing work?
33:44 - The different types of models
37:51 - Is value investing dead?
44:32 - What makes a good back test?
45:52 - Evolving an investment strategy over time
53:01 - The importance of risk management
54:39 - The one lesson Michael would teach the average investor

MICHAEL'S BOOK
https://www.amazon.com/Quantitative-Asset-Management-Investing-Institutional/dp/1264258445

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