Dynamic and Extreme Dependency Analysis Based on copula-GARCH and Semi Parametric Approach

Subject Areas : Financial Knowledge of Securities Analysis

Maryam  Moghaddas Bayat ¹ (دانشجوی دکتری دانشگاه الزهرا)س()
Shamsollah  Shirinbakhsh Massoleh ² (دانشیار دانشکده علوم اجتماعی واقتصادی دانشگاه الزهرا)س()

Received: 2015-08-30 Accepted : 2015-10-23 Published : 2016-04-03

Keywords: copula-GARCH, semi parametric approach, non-Gaussian conditional distr, extreme dependency structure,

Abstract :

This article uses copula-GARCH model and semi parametric approach to detach non-Gaussian conditional distribution to marginal densities and copula functions. This statistical characteristic conceives analysis of dynamic and extreme dependency in nonlinear and asymmetric structure. This modern statistical tool uses to study structure of Iran financial market dependency to domestic and international market during period of 3 August 2013 to 16 August 2015.Daily observations consist of Free Float Index, official exchange rate(Rial/Dollar), international gold price(in terms of Dollar), and OPEC Basket Price(Barrel/Dollar). Results show that stock exchange dependency to the markets is completely dynamic and there is non-correlation only in some time point. Structure of tail distribution dependency implies that there is asymmetric extreme dependency in a way that stock exchange dependency to the markets is stronger during expansion rather than recession. This findings show that investors are optimistic and more sensitive to good news during the period under study

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