TY - UNPD A1 - Corsi, Fulvio A1 - Kretschmer, Uta A1 - Mittnik, Stefan A1 - Pigorsch, Christian T1 - The volatility of realized volatility T2 - Center for Financial Studies (Frankfurt am Main): CFS working paper series ; No. 2005,33 N2 - Using unobservable conditional variance as measure, latent-variable approaches, such as GARCH and stochastic-volatility models, have traditionally been dominating the empirical finance literature. In recent years, with the availability of high-frequency financial market data modeling realized volatility has become a new and innovative research direction. By constructing "observable" or realized volatility series from intraday transaction data, the use of standard time series models, such as ARFIMA models, have become a promising strategy for modeling and predicting (daily) volatility. In this paper, we show that the residuals of the commonly used time-series models for realized volatility exhibit non-Gaussianity and volatility clustering. We propose extensions to explicitly account for these properties and assess their relevance when modeling and forecasting realized volatility. In an empirical application for S&P500 index futures we show that allowing for time-varying volatility of realized volatility leads to a substantial improvement of the model's fit as well as predictive performance. Furthermore, the distributional assumption for residuals plays a crucial role in density forecasting. Klassifikation: C22, C51, C52, C53 T3 - CFS working paper series - 2005, 33 KW - finance KW - realized volatility KW - realized quarticity KW - GARCH KW - normal inverse gaussian distribution KW - density forecasting KW - Volatilität Y1 - 2005 UR - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/2826 UR - https://nbn-resolving.org/urn:nbn:de:hebis:30-25891 ER -