EconPapers    
Economics at your fingertips  
 

Statistical inference for time-inhomogeneous volatility models

Danilo Mercurio and Vladimir G. Spokoiny

No 2002,61, SFB 373 Discussion Papers from Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes

Abstract: This paper offers a new approach for estimation and forecasting of the volatility of financial time series. No assumption is made about the parametric form of the processes, on the contrary we only suppose that the volatility can be approximated by a constant over some interval. In such a framework the main problem consists in filtering this interval of time homogeneity, then the estimate of the volatility can be simply obtained by local averaging. We construct a locally adaptive volatility estimate (LA VE) which can perform this task and investigate it both from the theoretical point of view and through Monte Carlo simulations. Finally the LAVE procedure is applied to a data set of nine exchange rates and a comparison with a standard GARCH model is also provided. Both models appear to be able of explaining many of the features of the data, nevertheless the new approach seems to be superior GARCH method as far' as the out of sample results are taken into consideration.

Keywords: stochastic volatility model; adaptive estimation; local homogeneity (search for similar items in EconPapers)
Date: 2002
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/65319/1/727037196.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:zbw:sfb373:200261

Access Statistics for this paper

More papers in SFB 373 Discussion Papers from Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().

 
Page updated 2025-03-20
Handle: RePEc:zbw:sfb373:200261