Value‐at‐risk under extreme values: the relative performance in MENA emerging stock markets
Value‐at‐risk under extreme values: the relative performance in MENA emerging stock markets
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DOI：
10.1108/17439130610657368
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发表时间：
2006-04
影响因子：
1.7
通讯作者：
A. Maghyereh;Haitham A. Al-Zoubi
中科院分区：
文献类型：
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作者：
A. Maghyereh;Haitham A. Al-Zoubi
目的-本文旨在研究最流行的风险价值（VaR）估计的相对表现，重点是极值理论（EVT）方法，为七个中东和北非（MENA）county.Design/方法/途径-本文计算的极值理论的收益率序列的尾部分布。这允许计算VaR并将结果与方差-协方差方法、历史模拟和正态分布、Student-t分布和偏态Student-t分布的E-T型过程进行比较。本文评估的模型，这是用于在风险值估计的性能，根据其经验failure rates.Findings -实证结果表明，中东和北非市场的回报分布的特点是厚尾，这意味着，风险值的措施依赖于正态分布会低估风险值。结果表明，极值方法，通过建模的收益率分布的尾部，是更相关的测量风险价值。
Purpose – The paper aims to investigate the relative performance of the most popular value‐at‐risk (VaR) estimates with an emphasis on the extreme value theory (EVT) methodology for seven Middle East and North Africa (MENA) countries.Design/methodology/approach – The paper calculates tails distributions of return series by EVT. This allows computing VaR and comparing the results with Variance‐Covariance method, Historical simulation, and ARCH‐type process with normal distribution, Student‐t distribution and skewed Student‐t distribution. The paper assesses the performance of the models, which are used in VaR estimations, based on their empirical failure rates.Findings – The empirical results demonstrate that the return distributions of the MENA markets are characterized by fat tails which implies that VaR measures relies on the normal distribution will underestimate VaR. The results suggest that the extreme value approach, by modeling the tails of the return distributions, are more relevant to measure VaR...