Generalized Autoregressive Score Model with Realized Measures of Volatility

12 Pages Posted: 4 Jul 2014 Last revised: 2 Feb 2015

See all articles by Zhuo Huang

Zhuo Huang

National School of Development, Peking University

Tianyi Wang

University of International Business and Economics (UIBE) - School of Banking and Finance

Xin Zhang

Sveriges Riksbank - Research Division

Date Written: May 9, 2014

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.

Suggested Citation

Huang, Zhuo and Wang, Tianyi and Zhang, Xin (Kelvin), Generalized Autoregressive Score Model with Realized Measures of Volatility (May 9, 2014). Available at SSRN: https://ssrn.com/abstract=2461831 or http://dx.doi.org/10.2139/ssrn.2461831

Zhuo Huang (Contact Author)

National School of Development, Peking University ( email )

No. 38 Xueyuan Road
Haidian District
Beijing, Beijing 100871
China

Tianyi Wang

University of International Business and Economics (UIBE) - School of Banking and Finance ( email )

No.10, Huixindong Street
Chaoyang District
Beijing, 100029
China

Xin (Kelvin) Zhang

Sveriges Riksbank - Research Division ( email )

S-103 37 Stockholm
Sweden

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