Second order asymptotics of aggregated log-elliptical risk
Probability
2014-12-12 v1 Computation
Abstract
In this paper we establish the error rate of first order asymptotic approximation for the tail probability of sums of log-elliptical risks. Our approach is motivated by extreme value theory which allows us to impose only some weak asymptotic conditions satisfied in particular by log-normal risks. Given the wide range of applications of the log-normal model in finance and insurance our result is of interest for both rare-event simulations and numerical calculations. We present numerical examples which illustrate that the second order approximation derived in this paper significantly improves over the first order approximation.
Keywords
Cite
@article{arxiv.1405.0605,
title = {Second order asymptotics of aggregated log-elliptical risk},
author = {D. Kortschak and E. Hashorva},
journal= {arXiv preprint arXiv:1405.0605},
year = {2014}
}
Comments
in press in Methodology and Computing in Applied Probability