期刊名称：HIER Discussion Paper Series / Harvard Institute of Economic Research
出版年度：2008
卷号：2008
出版社：Harvard Institute of Economic Research
摘要：This paper focuses on the analysis of long-memory properties of copula-based time series. We show via simulations that there exist Clayton coupula-based stationarty Markov processes that exhibit long memory on the level of copulas. This long memory is captured by an extremly slow hyperbolic decay of copula-based dependence measures between lagged values of the process. In contrast, Gaussian and Eyrand-Farlie-Gumbel-Mongenstern copulas always produce short-memory stationary Markov processes. Application of copula-based Markov processes to volatility modeling captures both non-linear conditional time variation aas well as long memory, thus providing an attractive generalization of GARCH models
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