A Realized RSDC Model

This paper introduces a new multivariate conditional volatility model for returns that utilizes realized covariance matrices. The model decomposes the conditional and realized covariance matrices into standard deviations and correlations matrices. On a first level, the univariate variances are estimated by a modified Generalized Autoregressive Conditional Heteroskedasticity (GARCH) that exploits intraday information. On the second level the conditional correlation matrices follows a regime switching Markov process. The inference of the regimes and the regime-switching correlations exploits the information contained in the realized correlation. An empirical application shows the ease of estimation and a forecasting exercise shows superior predictive ability when the high-frequency information is incorporated. ⇤Mailing address: Department of Economics, Campus Box 8110, North Carolina State University, Raleigh, 27695-8110, USA. e-mail: [email protected]. †Mailing address: Department of Economics, Campus Box 8110, North Carolina State University, Raleigh, 27695-8110, USA. e-mail: [email protected]. Web site: http://www4.ncsu.edu/⇠dpellet.