Estimating Stochastic Volatility Models Using a Discrete Non-linear Filter. Working paper #3

Adam Clements, Stan Hurn () and Scott White
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Scott White: National Centre for Econometric Research

No 3, NCER Working Paper Series from National Centre for Econometric Research

Abstract: Many approaches have been proposed for estimating stochastic volatility (SV) models, a number of which are filtering methods. While non-linear filtering methods are superior to linear approaches, non-linear filtering methods have not gained a wide acceptance in the econometrics literature due to their computational cost. This paper proposes a discretised non-linear filtering (DNF) algorithm for the estimation of latent variable models. It is shown that the DNF approach leads to significant computational gains relative to other procedures in the context of SV estimation without any associated loss in accuracy. It is also shown how a number of extensions to standard SV models can be accommodated within the DNF algorithm.

Keywords: non-linear filtering; stochastic volatility; state-space models; asymmetries; latent factors; two factor volatility models (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-ets
Date: 2006-08-15
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Persistent link: http://EconPapers.repec.org/RePEc:qut:auncer:2006-3

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