Localized Realized Volatility Modeling

• Activity Number: 604
• Type: Invited
• Date/Time: Thursday, August 5, 2010 : 8:30 AM to 10:20 AM
• Sponsor: Business and Economic Statistics Section
• Author(s): Ying Chen*+ and Wolfgang Haerdle and Uta Pigorsch
• Companies: National University of Singapore and Humboldt University in Berlin and Universitaet Mannheim
• Keywords: Adaptive Procedure ; Localized Autoregressive Modeling ; Realized Volatility

Abstract

With the recent availability of high-frequency financial data the long range dependence of volatility regained researchers' interest and has lead to the consideration of long memory models for realized volatility. The long range diagnosis of volatility may be also generated by the short memory models of volatility with nonstationarities. In this paper we adopt this view on the dependence structure of volatility and propose a localized procedure for modeling realized volatility. That is at each point in time we determine a past interval over which volatility is approximated by a local linear process. A simulation study shows that long memory processes as well as short memory processes with structural breaks can be well approximated by this local approach. Furthermore, using S&P500 data the local modelling approach outperforms long memory type models in terms of predictability.