Factor Models for Equity Returns

This post introduces factor models as a method for understanding and modeling equity returns. It details the mathematical formulation of linear factor models, explaining how asset returns can be decomposed into systematic factor exposures and idiosyncratic noise. The post discusses the benefits of factor models for covariance matrix estimation, reducing storage and computational complexity compared to empirical methods. It also explores their application in portfolio optimization by maximizing the Sharpe Ratio and decomposing performance attribution into parallel and orthogonal components.