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Testing For Embeddability By Stationary Reversible Continuous-Time Markov Processes

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Author Info

  • Florens, Jean-Pierre
  • Renault, Eric
  • Touzi, Nizar

Abstract

Given an observation of a discrete-time process {Yi,i = 0...n} assumed to be Markov, stationary, and time reversible, we develop a (conservative) test procedure of embeddability by a continuous-time reversible Markov process. The test statistic is derived from a set of moment inequality restrictions implied by the spectral properties of such continuous-time processes. Most interesting is that the embeddability condition of interest is a direct extension of the well-known embeddability problem by a two-state Markov chain. Empirical experiments show that the embeddability hypothesis is rejected more frequently for exchange rate daily data than for stock indices data.

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Bibliographic Info

Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 14 (1998)
Issue (Month): 06 (December)
Pages: 744-769

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Handle: RePEc:cup:etheor:v:14:y:1998:i:06:p:744-769_14

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Cited by:
  1. MEDDAHI, Nour, 2001. "An Eigenfunction Approach for Volatility Modeling," Cahiers de recherche 2001-29, Universite de Montreal, Departement de sciences economiques.
  2. Nour Meddahi & Éric Renault, 2000. "Temporal Aggregation of Volatility Models," CIRANO Working Papers 2000s-22, CIRANO.
  3. Yacine Aït-Sahalia, 2002. "Telling from Discrete Data Whether the Underlying Continuous-Time Model Is a Diffusion," Journal of Finance, American Finance Association, vol. 57(5), pages 2075-2112, October.
  4. Darolles, Serge & Florens, Jean-Pierre & Gourieroux, Christian, 2004. "Kernel-based nonlinear canonical analysis and time reversibility," Journal of Econometrics, Elsevier, vol. 119(2), pages 323-353, April.
  5. Dennis Kristensen, 2009. "Pseudo-Maximum Likelihood Estimation in Two Classes of Semiparametric Diffusion Models," CREATES Research Papers 2009-41, School of Economics and Management, University of Aarhus.
  6. Croux, Christophe & Renault, Eric & Werker, Bas, 2004. "Dynamic factor models," Journal of Econometrics, Elsevier, vol. 119(2), pages 223-230, April.
  7. Xiaohong Chen & Lars Peter Hansen & Jose A. Scheinkman, 2009. "Principal components and the long run," CeMMAP working papers CWP07/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  8. Darolles, Serge & Laurent, Jean-Paul, 2000. "Approximating payoffs and pricing formulas," Journal of Economic Dynamics and Control, Elsevier, vol. 24(11-12), pages 1721-1746, October.
  9. Hill, Jonathan B. & Aguilar, Mike, 2013. "Moment condition tests for heavy tailed time series," Journal of Econometrics, Elsevier, vol. 172(2), pages 255-274.

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