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A Copula-GARCH Model of Conditional Dependencies: Estimating Tehran Market Stock Exchange Value-at-Risk

机译:条件依赖的Copula-GARCH模型:估计德黑兰市场股票交易所的风险价值

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Modeling the dependency between stock market returns is a difficult task when returns follow a complicated dynamics. It is not easy to specify the multivariate distribution relating two or more return series. In this paper, a methodology based on fitting ARIMA, GARCH and ARMA-GARCH models and copula functions is applied. In such methodology, the dependency parameter can easily be rendered conditional and time varying. This method is used to the daily returns of five major stock markets (Telecom (TE), Sina darou (SI), Motojen (MO), Mellat bank (ME), and Esfahan oil refinery (ES)). Then Value-at-Risk of Tehran Stock Exchange portfolio including mentioned assets, is estimated.
机译:当收益遵循复杂的动态时,对股票市场收益之间的依存关系进行建模是一项艰巨的任务。指定涉及两个或多个收益序列的多元分布并不容易。在本文中,应用了一种基于拟合ARIMA,GARCH和ARMA-GARCH模型以及copula函数的方法。在这种方法中,可以很容易地使依赖参数成为有条件的并且随时间变化。该方法用于五个主要股票市场(电信(TE),新浪达鲁(SI),莫托延(MO),梅拉特银行(ME)和伊斯法罕炼油厂(ES))的日收益。然后估算包括上述资产在内的德黑兰证券交易所投资组合的风险价值。

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