Abstract

A new high-frequency realized stochastic volatility model is proposed. Apart from the standard daily-frequency stochastic volatility model, the high-frequency stochastic volatility model is fit to intraday returns by extensively incorporating the intraday volatility pattern and the reaction of intraday volatility to macroeconomic nnouncements. The daily realized volatility calculated using intraday returns is incorporated into the high-frequency stochastic volatility model by taking account of the bias in the daily realized volatility caused by microstructure noise. A Bayesian method via Markov chain Monte Carlo is developed for the analysis of the proposed model. The empirical analysis using the 5-minute returns of E-mini S&P 500 futures provides evidence that our high-frequency realized stochastic volatility model improves in-sample model fit and volatility forecasting over the high-frequency stochastic model without the daily realized volatility.