A0677
Title: Generalized autoregressive conditional betas
Authors: Francesco Violante - IESEG School of Management (France) [presenting]
Stefano Grassi - University of Rome 'Tor Vergata' (Italy)
Abstract: A new class of observation-driven models, the generalized autoregressive conditional betas (GACB), is proposed that describe the joint dynamics of the time-varying slopes in a system of conditionally heteroskedastic simultaneous multiple regressions. The GACB model accommodates large dimensions, parametric longitudinal restrictions, exogenous variables, and the coexistence of constant and time-varying slopes. It also introduces new mechanisms for the transmission of shocks, namely beta spillovers, which have economic significance. Stationarity and uniform invertibility conditions are derived and beta and covariance tracking constraints are presented. Several computationally convenient quasi-maximum likelihood estimators, both parallel and sequential, are proposed, and their finite sample properties are evaluated using extensive Monte Carlo experiments. Finally, the GACB model is applied to illustrate the role of beta spillovers in the Fama-French three-factor asset pricing model. The results demonstrate the usefulness of the GACB model in providing insight into the transmission of shocks in financial markets.
