Description

Book Synopsis

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,

Navigating the Factor Zoo

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    A Paperback by Michael Zhang

    £32.99

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      Book details

      Publisher Taylor & Francis
      Published 12 September 2024
      ISBN-13 9781032768410
      978-1032768410
      ISBN-10 103276841X
      Also in:
      Business, Finance & Law Investment and securities

      Description

      Book Synopsis

      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,

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