Long Range Dependence in Heavy Tailed Stochastic Processes
نویسنده
چکیده
The notion of long range dependence has traditionally been deened through a slow decay of correlations. This approach may be completely inappropriate in the case of a stochastic process with heavy tails. Yet long memory has been reported to be found in various elds where heavy tails are a standard feature of the commonly used stochastic models. Financial and communications networks data are among those often believed to exhibit long memory. We discuss alternative points of view on long range dependence that are applicable in the heavy tailed case. Such alternative approaches may be tailored for a particular applications at hand.
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