The volatility of realized volatility
- 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
Author: | Fulvio Corsi, Uta Kretschmer, Stefan Mittnik, Christian Pigorsch |
---|---|
URN: | urn:nbn:de:hebis:30-25891 |
Parent Title (German): | Center for Financial Studies (Frankfurt am Main): CFS working paper series ; No. 2005,33 |
Series (Serial Number): | CFS working paper series (2005, 33) |
Document Type: | Working Paper |
Language: | English |
Year of Completion: | 2005 |
Year of first Publication: | 2005 |
Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
Release Date: | 2006/05/02 |
Tag: | GARCH; density forecasting; finance; normal inverse gaussian distribution; realized quarticity; realized volatility |
GND Keyword: | Volatilität |
HeBIS-PPN: | 197420028 |
Institutes: | Wissenschaftliche Zentren und koordinierte Programme / Center for Financial Studies (CFS) |
Dewey Decimal Classification: | 3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft |
Licence (German): | ![]() |