Multiscale Asset Pricing: Integrating Wavelet Analysis and High Order Moments into the Fama-French Model

Abstract

This paper introduces a novel approach to asset pricing by integrating wavelet analysis, the Fama-French three-factor model, and high order moments into a multiscale pricing model. The primary aim is to investigate the influence of co-skewness and co-kurtosis systematic risks on the relationship between stock returns and Fama-French risk factors across different time scales. By leveraging multiresolution analysis, which decomposes data into components associated with varying time scales, the study evaluates and compares the performance of the traditional Fama-French model against the augmented model incorporating high order moments over diverse investment periods. The findings reveal that the inclusion of higher order moments enhances the explanatory power of the Fama-French three-factor model, particularly as the wavelet scale increases. Moreover, the relationship between portfolio returns and market risk factors, as well as size and value factors, exhibits significant variations depending on the time horizon under consideration. This underscores the importance of nonlinear market risk across different time scales, highlighting the dynamic nature of risk and return relationships. By emphasizing the multiscale property of risk and return dynamics, the paper provides valuable insights for investors, asset pricing researchers, and fund managers. It underscores the importance of adapting investment periods and portfolio management strategies in response to the varying nature of risk over different time scales. The proposed methodology, which utilizes multiresolution analysis, offers a new perspective on portfolio selection and investment strategies, empowering market participants to make more informed decisions in navigating the complexities of financial markets. Overall, this work contributes to advancing our understanding of asset pricing dynamics and offers practical implications for investment decision-making.