Home // International Journal On Advances in Systems and Measurements, volume 4, numbers 1 and 2, 2011 // View article
Authors:
Marvin Nakayama
Keywords: quantile; value-at-risk; Latin hypercube sampling; variance reduction; confidence interval
Abstract:
Quantiles, which are also known as values-at-risk in finance, are often used as risk measures. Latin hypercube sampling (LHS) is a variance-reduction technique (VRT) that induces correlation among the generated samples in such a way as to increase efficiency under certain conditions; it can be thought of as an extension of stratified sampling in multiple dimensions. This paper develops asymptotically valid confidence intervals for quantiles that are estimated via simulation using LHS.
Pages: 86 to 94
Copyright: Copyright (c) to authors, 2011. Used with permission.
Publication date: September 15, 2011
Published in: journal
ISSN: 1942-261x