Regime Shift Model by Three Types of Distribution Considering a Heavy Tail and Dependence

14 Pages Posted: 19 Aug 2014

See all articles by Jeongwoo Kim

Jeongwoo Kim

Economic Research Institute, Yonsei University

Date Written: August 17, 2014

Abstract

I adopt a regime shift model to investigate a shift of distribution of each regime during a time series data. Unlike previous studies, I applied three types of distribution to use a regime shift model, i.e., normal, GEV and stable distribution, which allows me to consider a heavy tail regime in the model. From some theoretical basis and empirical results, I find that the regime shift model in stable distribution is best appropriate. I also find that tail index of the innovation and dependence measure move together, implying dependence among a consecutive data may lead extreme event and vice versa.

Keywords: regime shift model, tail index, dependence measure, extreme event

JEL Classification: E44, G10, N20

Suggested Citation

kim, Jeongwoo, Regime Shift Model by Three Types of Distribution Considering a Heavy Tail and Dependence (August 17, 2014). Available at SSRN: https://ssrn.com/abstract=2481956 or http://dx.doi.org/10.2139/ssrn.2481956

Jeongwoo Kim (Contact Author)

Economic Research Institute, Yonsei University ( email )

50 Yonsei-Ro
Seoul, 120-749
Korea, Republic of (South Korea)
+82-10-3259-2263 (Phone)

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