Navigating the factor zoo: the science of quantitative investing

By:

Zhang, Michael

Contributor(s):

Material type: Text

TextPublication details: Routledge New York 2025Description: xiv, 296 pISBN:

9781032768410

Subject(s):

DDC classification:

332.63 ZHA

Summary: Bridging the gap between theoretical asset pricing and industry practices in factors and factor investing, Zhang et al. provides a comprehensive treatment of factors, along with industry insights on practical factor development. Chapters cover a wide array of topics, including the foundations of quantamentals, the intricacies of market beta, the significance of statistical moments, the principles of technical analysis, and the impact of market microstructure and liquidity on trading. Furthermore, it delves into the complexities of tail risk and behavioral finance, revealing how psychological factors affect market dynamics. The discussion extends to the sophisticated use of option trading data for predictive insights and the critical differentiation between outcome uncertainty and distribution uncertainty in financial decision-making. A standout feature of the book is its examination of machine learning's role in factor investing, detailing how it transforms data preprocessing, factor discovery, and model construction. Overall, this book provides a holistic view of contemporary financial markets, highlighting the challenges and opportunities in harnessing alternative data and machine learning to develop robust investment strategies. (https://www.routledge.com/Navigating-the-Factor-Zoo-The-Science-of-Quantitative-Investing/Zhang-Lu-Shi/p/book/9781032768410?srsltid=AfmBOopjZopxZv_rbVuN3kmTrUXcs4ZeMy6Te8D7EOdaObo3_7t4K_zF)

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	Finance & Accounting	332.63 ZHA (Browse shelf(Opens below))	1	Available		008486

Table of contents:

Preface

Chapter 1. Factor Investing

Chapter 2. Quantamentals

Chapter 3. Statistical Moments as Factors

Chapter 4. Market Beta

Chapter 5. Technical Analysis Factors

Chapter 6. Microstructure and Liquidity

Chapter 7. Tail Risk

Chapter 8. Behavioral Finance

Chapter 9. Option Information

Chapter 10. Uncertainty

Chapter 11. Alternative Data

Chapter 12. Machine Learning in Factor Investing

Epilogue

[https://www.routledge.com/Navigating-the-Factor-Zoo-The-Science-of-Quantitative-Investing/Zhang-Lu-Shi/p/book/9781032768410?srsltid=AfmBOopjZopxZv_rbVuN3kmTrUXcs4ZeMy6Te8D7EOdaObo3_7t4K_zF]

Bridging the gap between theoretical asset pricing and industry practices in factors and factor investing, Zhang et al. provides a comprehensive treatment of factors, along with industry insights on practical factor development.

Chapters cover a wide array of topics, including the foundations of quantamentals, the intricacies of market beta, the significance of statistical moments, the principles of technical analysis, and the impact of market microstructure and liquidity on trading. Furthermore, it delves into the complexities of tail risk and behavioral finance, revealing how psychological factors affect market dynamics. The discussion extends to the sophisticated use of option trading data for predictive insights and the critical differentiation between outcome uncertainty and distribution uncertainty in financial decision-making. A standout feature of the book is its examination of machine learning's role in factor investing, detailing how it transforms data preprocessing, factor discovery, and model construction. Overall, this book provides a holistic view of contemporary financial markets, highlighting the challenges and opportunities in harnessing alternative data and machine learning to develop robust investment strategies.

(https://www.routledge.com/Navigating-the-Factor-Zoo-The-Science-of-Quantitative-Investing/Zhang-Lu-Shi/p/book/9781032768410?srsltid=AfmBOopjZopxZv_rbVuN3kmTrUXcs4ZeMy6Te8D7EOdaObo3_7t4K_zF)

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