WAVELET BETAS AT THE SECTOR LEVEL: A LENS TO CAPTURE RISK DYNAMICS THAT STANDARD BETAS IGNORE

The application of the CAPM to ten S&P sectors is investigated using wavelet analysis. Wavelet methods provide a unified framework for investigating the relationship among variables at different frequencies and the evolution of these relationships over time. Betas at different time and frequency scales using wavelet analysis are estimated for ten sectors and compared to the betas estimated from a simple regression of the market model. We find coherence and frequency differences across sectors that are not reflected in the estimation of standard beta. Given that there is no a priori reason to assume that the synchronization of sector returns with market returns has only a time varying dimension, wavelet analysis by allowing for multiple time-varying frequencies offers estimates of sector level betas that capture features of the underlying risk dynamics that would be missed using the standard estimate of beta.