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2024 | OriginalPaper | Chapter

How to Deal with Tail Dependence of Mixture Copula with an Extreme Weight

Authors : Sundusit Saekow, Phisanu Chiawkhun, Woraphon Yamaka, Nawapon Nakharutai, Parkpoom Phetpradap

Published in: Applications of Optimal Transport to Economics and Related Topics

Publisher: Springer Nature Switzerland

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Abstract

Tail dependence is the tool to measure dependence in the extremes of a bivariate distribution. Copula is the function used to describe the dependence between the variables. Therefore, copula is used in order to determine the tail dependence. In this work, we focus on dealing with the case of an extreme weight of mixture copula. We provide the transformed Bayesian model averaging to estimate the tail dependence comparing with the conventional ways to estimate the mixture copula by simulation study.

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previous chapter A Quantile Regression for Computer Crimes Act in Thailand
next chapter An Analysis of Volatility Spillover Effect Between Energy and Agricultural Markets
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Metadata
Title
How to Deal with Tail Dependence of Mixture Copula with an Extreme Weight
Authors
Sundusit Saekow
Phisanu Chiawkhun
Woraphon Yamaka
Nawapon Nakharutai
Parkpoom Phetpradap
Copyright Year
2024
Book
Applications of Optimal Transport to Economics and Related Topics

Print ISBN: 978-3-031-67769-4

Electronic ISBN: 978-3-031-67770-0

Copyright Year: 2024

DOI
https://doi.org/10.1007/978-3-031-67770-0_43

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