Copulas, Tail Dependence and Applications to the Analysis of Financial Time Series View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2013

AUTHORS

Fabrizio Durante

ABSTRACT

Tail dependence is an important property of a joint distribution function that has a huge impact on the determination of risky quantities associated to a stochastic model (Value-at-Risk, for instance). Here we aim at presenting some investigations about tail dependence including the following aspects: the determination of suitable stochastic models to be used in extreme scenarios; the notion of threshold copula, that helps in describing the tail of a joint distribution. Possible applications of the introduced concepts to the analysis of financial time series are presented with particular emphasis on cluster methods and determination of possible contagion effects among markets. More... »

PAGES

17-22

Book

TITLE

Aggregation Functions in Theory and in Practise

ISBN

978-3-642-39164-4
978-3-642-39165-1

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-39165-1_3

DOI

http://dx.doi.org/10.1007/978-3-642-39165-1_3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1038305947


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