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

  • Adam Clements
  • Stan Hurn
  • Scott White

    (National Centre for Econometric Research)

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.

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File URL: http://www.ncer.edu.au/papers/documents/WPNo3.pdf
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Paper provided by National Centre for Econometric Research in its series NCER Working Paper Series with number 3.

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Date of creation: 15 Aug 2006
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Handle: RePEc:qut:auncer:2006-3
Contact details of provider: Phone: 07 3138 5066
Fax: 07 3138 1500
Web page: http://www.ncer.edu.au

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