%0 Electronic Book %A Kim, Jeongwoo %I SSRN %C S.l. %D 2014 %G English %~ Galerie für Zeitgenössische Kunst Leipzig %T Regime Shift Model by Three Types of Distribution Considering a Heavy Tail and Dependence %U https://doi.org/10.2139/ssrn.2481956 %U https://ssrn.com/abstract=2481956 %X 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 %Z https://katalog.gfzk.de/Record/0-1792231121 %U https://katalog.gfzk.de/Record/0-1792231121