Value at risk (VaR) is a commonly used tool to measure market risk. In this paper, we discuss the problems of model choice and VaR performance. The VaRs of daily returns of the Shanghai and Shenzhen indexes are calculated using equally weighted moving average (EQMA), exponentially weighted moving average (EWMA), GARCH(1,1), empirical density estimation method, and the Pareto-type extreme-value distribution methods. Considering the length of the window and the requirement for adequate capital, back testing indicates that the Pareto-type extreme-value distribution method reflects the real market risk more accurately than the other models.
Quality & Quantity – Springer Journals
Published: Feb 7, 2008
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