Value-at-risk time scaling: a Monte Carlo approach

Moepa Malataliana and Michael Rigotard

Journal of Risk Model Validation

Abstract: ABSTRACTThis paper discusses a value-at-risk (VaR) time-scaling approach based on fitting a distribution function so as to apply a Monte Carlo simulation to determine long-term VaR. The paper uses composite normal-Pareto distribution to better capture tail risk. Due to the material model risk inherent in the long-term VaR calculation, kernel distribution is used as a benchmark distribution.;

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