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Heavy-tailed value-at-risk analysis for Malaysian stock exchange

  • Chin, Wen Cheong

This article investigates the comparison of power-law value-at-risk (VaR) evaluation with quantile and non-linear time-varying volatility approaches. A simple Pareto distribution is proposed to account the heavy-tailed property in the empirical distribution of returns. Alternative VaR measurement such as non-parametric quantile estimate is implemented using interpolation method. In addition, we also used the well-known two components ARCH modelling technique under the assumptions of normality and heavy-tailed (student-t distribution) for the innovations. Our results evidenced that the predicted VaR under the Pareto distribution exhibited similar results with the symmetric heavy-tailed long-memory ARCH model. However, it is found that only the Pareto distribution is able to provide a convenient framework for asymmetric properties in both the lower and upper tails.

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Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

Volume (Year): 387 (2008)
Issue (Month): 16 ()
Pages: 4285-4298

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Handle: RePEc:eee:phsmap:v:387:y:2008:i:16:p:4285-4298
Contact details of provider: Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

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