Product autoregressive models for non-negative variables
When variables in time series context are non-negative, such as for volatility, survival time or wave heights, a multiplicative autoregressive model of the type Xt=Xt−1αVt, 0≤α<1,t=1,2,… may give the preferred dependent structure. In this paper, we study the properties of such models and propose methods for parameter estimation. Explicit solutions of the model are obtained in the case of gamma marginal distribution.
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Volume (Year): 82 (2012)
Issue (Month): 8 ()
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References listed on IDEAS
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- Bauwens, Luc & Veredas, David, 2004.
"The stochastic conditional duration model: a latent variable model for the analysis of financial durations,"
Journal of Econometrics,
Elsevier, vol. 119(2), pages 381-412, April.
- BAUWENS, Luc & VEREDAS, David, "undated". "The stochastic conditional duration model: a latent variable model for the analysis of financial durations," CORE Discussion Papers RP 1688, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Robert Engle, 2002. "New frontiers for arch models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 425-446.
- Maria Pacurar, 2008. "Autoregressive Conditional Duration Models In Finance: A Survey Of The Theoretical And Empirical Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 22(4), pages 711-751, 09. Full references (including those not matched with items on IDEAS)
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