Generalized Autoregressive Score Model with Realized Measures of Volatility

Abstract

We propose a new observation-driven time-varying parameter framework to model the financial return and realized variance jointly. The latent dynamic factor is updated by the scaled local density score as a function of past daily return and realized variance. The new model shares the advantages of both the GAS model of Creal et al. (2013) and Realized GARCH model of Hansen et al. (2012). It is robust to extreme outliers in observations as the volatility dynamics is related to the heavy-tailedness of innovation density. In the meanwhile, it adapts quickly to drastic volatility changes by incorporating realized measures of volatility based on high frequency data. We apply the model to a number of equity returns and demonstrate its promising performance, even during the 2008 financial crisis.

Keywords: Generalized Autoregressive Score; High-frequency data; Realized GARCH; Extreme observations.

JEL Classification: C10, C22.