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

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Author Info
Adam Clements
Scott White (School of Economics and Finance, Queensland University of Technology)

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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.

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Paper provided by School of Economics and Finance, Queensland University of Technology in its series School of Economics and Finance Discussion Papers and Working Papers Series with number 191.

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Date of creation: 15 Jun 2005
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Handle: RePEc:qut:dpaper:191

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

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  3. Longin, Francois M, 1997. "The Threshold Effect in Expected Volatility: A Model Based on Asymmetric Information," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 10(3), pages 837-69.
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  7. Ghysels, E. & Harvey, A. & Renault, E., 1996. "Stochastic Volatility," Cahiers de recherche 9613, Universite de Montreal, Departement de sciences economiques. [Downloadable!]
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  8. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June. [Downloadable!] (restricted)
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  9. So, Mike K P & Li, W K & Lam, K, 2002. "A Threshold Stochastic Volatility Model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(7), pages 473-500, November.
  10. Watanabe, Toshiaki, 1999. "A Non-linear Filtering Approach to Stochastic Volatility Models with an Application to Daily Stock Returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(2), pages 101-21, March-Apr. [Downloadable!]
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  12. Friedman, Moshe & Harris, Lawrence, 1998. "A Maximum Likelihood Approach for Non-Gaussian Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 284-91, July.
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