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Non-linear filtering with state dependant transition probabilities: A threshold (size effect) SV model

Author

Listed:
  • Adam Clements
  • Scott White

    (School of Economics and Finance, Queensland University of Technology)

Abstract

This paper considers the size effect, where volatility dynamics are dependant upon the current level of volatility within an stochastic volatility framework. A non-linear filtering algorithm is proposed where the dynamics of the latent variable is conditioned on its current level. This allows for the estimation of a stochastic volatility model where dynamics are dependant on the level of volatility. Empirical results suggest that volatility dynamics are in fact influenced by the level of prevailing volatility. When volatility is relatively low (high), volatility is extremely (not) persistent with little (a great deal of) noise.

Suggested Citation

  • Adam Clements & Scott White, 2005. "Non-linear filtering with state dependant transition probabilities: A threshold (size effect) SV model," School of Economics and Finance Discussion Papers and Working Papers Series 191, School of Economics and Finance, Queensland University of Technology.
  • Handle: RePEc:qut:dpaper:191
    as

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    File URL: http://external-apps.qut.edu.au/business/documents/discussionPapers/2005/No%20191%20-%20Clements.pdf
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    References listed on IDEAS

    as
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    Keywords

    Non-linear filtering; stochastic volatility; size effect; threshold;

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