Michael Zhang is the founder of Super Quantum Fund. He has over 20 years of experience in quantitative investing. He publishes in the most prestigious academic journals and has been highly cited. He holds a PhD from MIT, an MSc, and two bachelor’s degrees from Tsinghua University.Tao Lu is the CEO of Super Quantum Fund. He has extensive practical experience in portfolio management through quantitative methods and leading quantitative research teams. He holds a PhD from the Chinese University of Hong Kong and two bachelor’s degrees from Tsinghua University.Chuan Shi is the chief data scientist at Beijing Liangxin Investment Management, specializing in factor investing, portfolio allocation, and risk management. He holds a PhD from MIT and bachelor's and master's degrees from Tsinghua University. He is the lead author of "Factor Investing: Methodology and Practice."

This book delivers a rigorous and stimulating discussion of fundamental questions. What does a human know that a machine learning algorithm cannot possibly know and vice versa? When does a serious investor know enough to act and when does the irreducible uncertainty lead to caution? This book offers a deeply insightful window into the modern frontier, and how to think about balancing sophisticated algorithms with practical challenges at the edges.Shane Greenstein, PhDProfessorHarvard Business SchoolFactor investing is the cornerstone of active portfolio management. For both students and investment professionals, this book provides a comprehensive analysis of the foundations of factor investing as well as practical implementation. Importantly, the authors detail not just the investment opportunities but also the risks. Recommended.Campbell Harvey, PhDProfessorDuke UniversityInformation technology has transformed most areas of finance, including driving the growth of quantitative investing. This book provides a survey of the different kinds of data and factors behind this trend. The book’s overview of the science, art, technology, and techniques helps the reader comprehensively understand the current knowledge frontier while pointing out future directions for research and practice. Terrence Hendershott, PhDProfessorUniversity of California, BerkeleyIt is instantly clear that the authors combine deep academic knowledge with a wealth of practical market experience. What really sets this book apart, however, is that they are not just telling you what used to work in the past, but try to look to the future – what new methods and ways of thinking will deepen our understanding of financial markets.Yuriy Nevmyvaka, PhDManaging Director, Head of Machine Learning Research, Morgan StanleyIvory Tower meets Wall Street – Tapping into their wealth of knowledge and experience as both academics and hedge fund managers, the authors cover a multitude of factors that affect returns in the financial market. Packed with academic rigor and practical relevance, this is an important and compelling read. Michael Saunders, PhDProfessorStanford UniversityA well-curated exploration of factor investing, systematically charting a map of important sources of financial returns. It is a solid treatment of how certainty can be generated from the uncertain financial world and an essential read for practitioners and students seeking a deeper understanding of quantitative investing.Feng Zhu, PhDProfessorHarvard Business School

• Table of ContentsPrefaceChapter 1. Factor InvestingChapter 2. QuantamentalsChapter 3. Statistical Moments as FactorsChapter 4. Market BetaChapter 5. Technical Analysis FactorsChapter 6. Microstructure and LiquidityChapter 7. Tail RiskChapter 8. Behavioral FinanceChapter 9. Option InformationChapter 10. UncertaintyChapter 11. Alternative DataChapter 12. Machine Learning in Factor InvestingEpilogue

Michael Zhang is the founder of Super Quantum Fund. He has over 20 years of experience in quantitative investing. He publishes in the most prestigious academic journals and has been highly cited. He holds a PhD from MIT, an MSc, and two bachelor’s degrees from Tsinghua University.Tao Lu is the CEO of Super Quantum Fund. He has extensive practical experience in portfolio management through quantitative methods and leading quantitative research teams. He holds a PhD from the Chinese University of Hong Kong and two bachelor’s degrees from Tsinghua University.Chuan Shi is the chief data scientist at Beijing Liangxin Investment Management, specializing in factor investing, portfolio allocation, and risk management. He holds a PhD from MIT and bachelor's and master's degrees from Tsinghua University. He is the lead author of "Factor Investing: Methodology and Practice."

This book delivers a rigorous and stimulating discussion of fundamental questions. What does a human know that a machine learning algorithm cannot possibly know and vice versa? When does a serious investor know enough to act and when does the irreducible uncertainty lead to caution? This book offers a deeply insightful window into the modern frontier, and how to think about balancing sophisticated algorithms with practical challenges at the edges.Shane Greenstein, PhDProfessorHarvard Business SchoolFactor investing is the cornerstone of active portfolio management. For both students and investment professionals, this book provides a comprehensive analysis of the foundations of factor investing as well as practical implementation. Importantly, the authors detail not just the investment opportunities but also the risks. Recommended.Campbell Harvey, PhDProfessorDuke UniversityInformation technology has transformed most areas of finance, including driving the growth of quantitative investing. This book provides a survey of the different kinds of data and factors behind this trend. The book’s overview of the science, art, technology, and techniques helps the reader comprehensively understand the current knowledge frontier while pointing out future directions for research and practice. Terrence Hendershott, PhDProfessorUniversity of California, BerkeleyIt is instantly clear that the authors combine deep academic knowledge with a wealth of practical market experience. What really sets this book apart, however, is that they are not just telling you what used to work in the past, but try to look to the future – what new methods and ways of thinking will deepen our understanding of financial markets.Yuriy Nevmyvaka, PhDManaging Director, Head of Machine Learning Research, Morgan StanleyIvory Tower meets Wall Street – Tapping into their wealth of knowledge and experience as both academics and hedge fund managers, the authors cover a multitude of factors that affect returns in the financial market. Packed with academic rigor and practical relevance, this is an important and compelling read. Michael Saunders, PhDProfessorStanford UniversityA well-curated exploration of factor investing, systematically charting a map of important sources of financial returns. It is a solid treatment of how certainty can be generated from the uncertain financial world and an essential read for practitioners and students seeking a deeper understanding of quantitative investing.Feng Zhu, PhDProfessorHarvard Business School

• Table of ContentsPrefaceChapter 1. Factor InvestingChapter 2. QuantamentalsChapter 3. Statistical Moments as FactorsChapter 4. Market BetaChapter 5. Technical Analysis FactorsChapter 6. Microstructure and LiquidityChapter 7. Tail RiskChapter 8. Behavioral FinanceChapter 9. Option InformationChapter 10. UncertaintyChapter 11. Alternative DataChapter 12. Machine Learning in Factor InvestingEpilogue