Parameterization of Copulas and Covariance Decay of Stochastic Processes with Applications

Details Parameterization of Copulas and Covariance Decay of Stochastic Processes with Applications Parameterization of Copulas and Covariance Decay of Stochastic Processes with Applications

2012-04-16

arxiv.org/abs/1204.3339v1

Mathematics

Statistics Theory

Scientific paper

In this work we study the problem of constructing stochastic processes with a predetermined covariance decay by parameterizing its marginals and a given family of copulas. We present several examples to illustrate the theory, including the important Gaussian and Euclidean families of copulas. We associate the theory to common applied time series models and present a general methodology to estimate a given parameter of interest identifiable through the process' covariance decay. To exemplify the proposed methodology, we present simple Monte Carlo applications to parameter estimation in time series. The methodology is also applied to the S&P500 US stock market index.

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