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Nonlinearity and Temporal Dependence Author info | Abstract | Publisher info | Download info | Related research | Statistics Xiaohong Chen () (Cowles Foundation, Yale University )
Lars P. Hansen (Dept. of Economics and Statistics, University of Chicago)
Marine Carrasco (Dept. of Economics, University of Montreal)
Additional information is available for the following
registered author(s):
Nonlinearities in the drift and diffusion coefficients influence temporal dependence in scalar diffusion models. We study this link using two notions of temporal dependence: beta-mixing and rho-mixing. We show that beta-mixing and rho-mixing with exponential decay are essentially equivalent concepts for scalar diffusions. For stationary diffusions that fail to be rho-mixing, we show that they are still beta-mixing except that the decay rates are slower than exponential. For such processes we find transformations of the Markov states that have finite variances but infinite spectral densities at frequency zero. Some have spectral densities that diverge at frequency zero in a manner similar to that of stochastic processes with long memory. Finally we show how nonlinear, state-dependent, Poisson sampling alters the unconditional distribution as well as the temporal dependence.
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Paper provided by Cowles Foundation, Yale University in its series Cowles Foundation Discussion Papers with number
1652.
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Length: 31 pages
Date of creation: May 2008Date of revision:
Handle: RePEc:cwl:cwldpp:1652Contact details of provider: Postal: Yale University, Box 208281, New Haven, CT 06520-8281 USA Phone: (203) 432-3702 Fax: (203) 432-6167 Web page: http://cowles.econ.yale.edu/ More information through EDIRC
Order Information: Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA
For technical questions regarding this item, or to correct its listing, contact: (Glena Ames).
Keywords: Mixing ; Diffusion ; Strong dependence ; Long memory ; Poisson sampling ; Other versions of this item:
Paper Xiaohong Chen & Lars P. Hansen & Marine Carrasco, 2009.
"Nonlinearity and Temporal Dependence ,"
CIRANO Working Papers
2009s-17, CIRANO.
[Downloadable!] Chen, Xiaohong & Hansen, Lars Peter & Carrasco, Marine, 2008.
"Nonlinearity and Temporal Dependence ,"
Working Papers
48, Yale University, Department of Economics.
[Downloadable!] Find related papers by JEL classification: C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
This paper has been announced in the following NEP Reports :
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"Estimation of Copula-Based Semiparametric Time Series Models ,"
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CIRANO Working Papers
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Other versions:
Chernov, Mikhail & Gallant, A. Ronald & Ghysels, Eric & Tauchen, George, 2002.
"Alternative Models for Stock Price Dynamic ,"
Working Papers
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[Downloadable!] Chernov, Mikhail & Ronald Gallant, A. & Ghysels, Eric & Tauchen, George, 2003.
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[Downloadable!] (restricted) Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2002.
"Parametric and Nonparametric Volatility Measurement ,"
Center for Financial Institutions Working Papers
02-27, Wharton School Center for Financial Institutions, University of Pennsylvania.
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Other versions: Dominique Guegan, 2005.
"How can we define the concept of long memory ? An econometric survey ,"
Post-Print
halshs-00179343_v1, HAL.
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Other versions: Carrasco, Marine & Chernov, Mikhaël & Florens, Jean-Pierre & Ghysels, Eric, 2000.
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