Dynamic conditional betas and equity returns

Our study makes use of a new approach to estimate time-varyingbetas with an application of the corrected Dynamic Conditional Correlation (cDCC) model. Our empirical methodology encompasses an examination of predictive relations between equity return and different specifications of dynamic conditional beta, using cross-sectional regression analysis at both the portfolio and firm levels. Our main finding is a significant, positive relation between equity excess return and an interactive cross product term of dynamic conditional beta and market excess return ([Formula: see text]); suggesting that equity return is largely determined by an interaction effect between dynamic beta and market return.

Asset Pricing Models with Conditional Betas and Alphas: The Effects of Data Snooping and Spurious Regression

This paper studies the estimation of asset pricing model regressions with conditional alphas and betas, focusing on the joint effects of data snooping and spurious regression. We find that the regressions are reasonably well specified for conditional betas, even in settings where simple predictive regressions are severely biased. However, there are biases in estimates of the conditional alphas. When time-varying alphas are suppressed and only time-varying betas are considered, the betas become biased. Previous studies overstate the significance of time-varying alphas.