The volatility of realized volatility

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: CFS Working Paper ; No. 2005/33

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes ; Model Construction and Estimation ; Model Evaluation, Validation, and Selection ; Forecasting Models; Simulation Methods
• Subject: Finance ; Realized Volatility ; Realized Quarticity ; GARCH ; Normal Inverse Gaussian Distribution ; Density Forecasting

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Corsi, Fulvio ; Kretschmer, Uta ; Mittnik, Stefan ; Pigorsch, Christian
• Event: Veröffentlichung
• (who): Goethe University Frankfurt, Center for Financial Studies (CFS)
• (where): Frankfurt a. M.
• (when): 2005

Further information

• Handle: http://hdl.handle.net/10419/25467
• URN: urn:nbn:de:hebis:30-25891
• Last update: 10.03.2025, 11:44 AM CET