Heavy-tailed value-at-risk analysis for Malaysian stock exchange
AbstractThis 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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Bibliographic InfoArticle provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.
Volume (Year): 387 (2008)
Issue (Month): 16 ()
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Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/
Value-at-risk; Heavy-tail distribution; ARCH models; Financial time series;
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