Non linearity and temporal dependence

作者：Chen Xiaohong^*; Hansen Lars Peter; Carrasco Marine

来源：Journal of Econometrics, 2010, 155(2): 155-169.

DOI：10.1016/j.jeconom.2009.10.001

• Diffusion
• Strong dependence
• Long memory
• Poisson sampling
• Quadratic forms

Nonlinearities in the drift and diffusion coefficients influence temporal dependence in diffusion models. We study this link using three measures of temporal dependence: rho-mixing, beta-mixing and alpha-mixing. Stationary diffusions that are rho-mixing have mixing coefficients that decay exponentially to zero. When they fail to be rho-mixing, they are still beta-mixing and alpha-mixing; but coefficient decay is slower than exponential. For such processes we find transformations of the Markov states that have finite variances but infinite spectral densities at frequency zero. The resulting spectral densities behave like those of stochastic processes with long memory. Finally we show how state dependent, Poisson sampling alters the temporal dependence.

• 出版日期2010-4