Kernel-based nonlinear canonical analysis and time reversibility
We consider a kernel-based approach to nonlinear canonical correlation analysis and its implementation for time series. We deduce a test procedure of the reversibility hypothesis. The method is applied to the analysis of stochastic differential equation from high-frequency data on stock returns.
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- Darolles, Serge & Gourieroux, Christian, 2001.
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- Serge Darolles & Christian Gourieroux, 2000. "Truncated dynamics and estimation of diffusion equations," Post-Print halshs-00678232, HAL.
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"Nonparametric Instrumental Regression,"
Cahiers de recherche
2002-05, Universite de Montreal, Departement de sciences economiques.
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- Darolles, Serge & Fan, Yanqin & Florens, Jean-Pierre & Renault, Eric, 2003. "Non Parametric Instrumental Regression," IDEI Working Papers 228, Institut d'Économie Industrielle (IDEI), Toulouse, revised 2010.
- Serge Darolles & Jean-Pierre Florens & Yanqin Fan & Eric Renault, 2011. "Nonparametric Instrumental Regression," Post-Print halshs-00677716, HAL.
- Florens, Jean-Pierre & Renault, Eric & Touzi, Nizar, 1998. "Testing For Embeddability By Stationary Reversible Continuous-Time Markov Processes," Econometric Theory, Cambridge University Press, vol. 14(06), pages 744-769, December.
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"Approximating payoffs and pricing formulas,"
- Hansen, Lars Peter & Alexandre Scheinkman, Jose & Touzi, Nizar, 1998. "Spectral methods for identifying scalar diffusions," Journal of Econometrics, Elsevier, vol. 86(1), pages 1-32, June.
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