Author:
Das Bikramjit,Mitra Abhimanyu,Resnick Sidney
Abstract
Multivariate regular variation plays a role in assessing tail risk in diverse applications such as finance, telecommunications, insurance, and environmental science. The classical theory, being based on an asymptotic model, sometimes leads to inaccurate and useless estimates of probabilities of joint tail regions. This problem can be partly ameliorated by using hidden regular variation (see Resnick (2002) and Mitra and Resnick (2011)). We offer a more flexible definition of hidden regular variation that provides improved risk estimates for a larger class of tail risk regions.
Publisher
Cambridge University Press (CUP)
Subject
Applied Mathematics,Statistics and Probability
Reference22 articles.
1. Estimation of extreme risk regions under multivariate regular variation
2. Hidden regular variation and the rank transform
3. [16] Mitra A. and Resnick S. I. (2010). Hidden regular variation: detection and estimation. Preprint. Available at http://arxiv.org/abs/1001.5058v2.
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22 articles.
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