Simulated maximum likelihood for general stochastic volatility models: a change of variable approach

Tore Kleppe (tore.kleppe@uis.no) and Hans J. Skaug

MPRA Paper from University Library of Munich, Germany

Abstract: Maximum likelihood has proved to be a valuable tool for fitting the log-normal stochastic volatility model to financial returns time series. Using a sequential change of variable framework, we are able to cast more general stochastic volatility models into a form appropriate for importance samplers based on the Laplace approximation. We apply the methodology to two example models, showing that efficient importance samplers can be constructed even for highly non-Gaussian latent processes such as square-root diffusions.

Keywords: Change of Variable; Heston Model; Laplace Importance Sampler; Simulated Maximum Likelihood; Stochastic Volatility (search for similar items in EconPapers)
JEL-codes: C13 C22 (search for similar items in EconPapers)
Date: 2008-07-10
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:12022

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