Clustering of volatility in variable diffusion processes

Gemunu H. Gunaratne, Matthew Nicol, Lars Seemann and Andrei Török

Physica A: Statistical Mechanics and its Applications, 2009, vol. 388, issue 20, 4424-4430

Abstract: Increments in financial markets have anomalous statistical properties including fat-tailed distributions and volatility clustering (i.e., the autocorrelation functions of return increments decay quickly but those of the squared increments decay slowly). One of the central questions in financial market analysis is whether the nature of the underlying stochastic process can be deduced from these statistical properties. We have shown previously that a class of variable diffusion processes has fat-tailed distributions. Here we show analytically that such models also exhibit volatility clustering. To our knowledge, this is the first case where clustering of volatility is proven analytically in a model.

Keywords: Variable diffusion processes; Clustering of volatility; Financial markets; Stochastic differential equations (search for similar items in EconPapers)
Date: 2009
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:388:y:2009:i:20:p:4424-4430

DOI: 10.1016/j.physa.2009.06.050

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