Asset pricing with time-varying betas for stocks traded on S&P 500

This study uses a novel approach for capturing time variation in betas whose pattern is treated as a function of market returns. A two-factor model (TFM) is constructed using estimated coefficients of a nonlinear regression. The model is tested against the CAPM and the Fama and French three-factor model in the context of time series regressions. The used stocks are traded on S&P 500. The period spans from 1993 to 2011. The time series regression results depict the superiority of the TFM in explaining portfolio returns including momentum ones. We also provide evidence that the particular portfolios employed at the construction of the new model accommodate different fundamental characteristics and different risk levels.