Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Efficient calculation of risk measures by importance sampling -- the
  heavy tailed case   Computation of extreme quantiles and tail-based risk measures using standard
Monte Carlo simulation can be inefficient. A method to speed up computations is
provided by importance sampling. We show that importance sampling algorithms,
designed for efficient tail probability estimation, can significantly improve
Monte Carlo estimators of tail-based risk measures. In the heavy-tailed
setting, when the random variable of interest has a regularly varying
distribution, we provide sufficient conditions for the asymptotic relative
error of importance sampling estimators of risk measures, such as Value-at-Risk
and expected shortfall, to be small. The results are illustrated by some
numerical examples.

16
The categories of this paper are: stat
33
The categories of this paper are: plasm-ph
35
The categories of this paper are: mtrl-th
21
The categories of this paper are: adap-org
31
The categories of this paper are: ao-sci
26
The categories of this paper are: bayes-an
36
The categories of this paper are: cmp-lg
19
The categories of this paper are: eess
30
The categories of this paper are: q-alg
5
The categories of this paper are: gr-qc
8
The categories of this paper are: hep-ex
22
The categories of this paper are: chao-dyn
4
The categories of this paper are: cond-mat
29
The categories of this paper are: funct-an
34
The categories of this paper are: chem-ph
3
The categories of this paper are: physics