We present several notions of high-level dependence for stochastic processes,
which have appeared in the literature. We calculate such measures for discrete
and continuous-time models, where we concentrate on time series with heavy-tailed
marginals, where extremes are likely to occur in clusters. Such models include linear
models and solutions to random recurrence equations; in particular, discrete and
continuous-time moving average and (G)ARCH processes. To illustrate our results
we present a small simulation study.
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We present several notions of high-level dependence for stochastic processes,
which have appeared in the literature. We calculate such measures for discrete
and continuous-time models, where we concentrate on time series with heavy-tailed
marginals, where extremes are likely to occur in clusters. Such models include linear
models and solutions to random recurrence equations; in particular, discrete and
continuous-time moving average and (G)ARCH processes. To illustrate our results
we pres...
»