Paper Info
Title
Accounting for secondary uncertainty: efficient computation of portfolio risk measures on multi and many core architectures.
Abstract
Aggregate Risk Analysis is a computationally intensive and a data intensive problem, thereby making the application of high-performance computing techniques interesting. In this paper, the design and implementation of a parallel Aggregate Risk Analysis algorithm on multi-core CPU and many-core GPU platforms are explored. The efficient computation of key risk measures, including Probable Maximum Loss (PML) and the Tail Value-at-Risk (TVaR) in the presence of both primary and secondary uncertainty for a portfolio of property catastrophe insurance treaties is considered. Primary Uncertainty is the the uncertainty associated with whether a catastrophe event occurs or not in a simulated year, while Secondary Uncertainty is the uncertainty in the amount of loss when the event occurs. A number of statistical algorithms are investigated for computing secondary uncertainty. Numerous challenges such as loading large data onto hardware with limited memory and organising it are addressed. The results obtained from experimental studies are encouraging. Consider for example, an aggregate risk analysis involving 800,000 trials, with 1,000 catastrophic events per trial, a million locations, and a complex contract structure taking into account secondary uncertainty. The analysis can be performed in just 41 seconds on a GPU, that is 24x faster than the sequential counterpart on a fast multi-core CPU. The results indicate that GPUs can be used to efficiently accelerate aggregate risk analysis even in the presence of secondary uncertainty.
Year
DOI
Venue
2013
10.1145/2535557.2535562
WHPCF@SC
Keywords
DocType
Volume
data intensive problem,portfolio risk measure,account secondary uncertainty,efficient computation,core architecture,primary uncertainty,fast multi-core,secondary uncertainty,high-performance computing technique,catastrophe event,aggregate risk analysis,key risk measure,catastrophic event,gpu computing,risk analytics,risk management,parallel computing
Journal
abs/1310.2274
Citations 
PageRank 
References 
0
0.34
5
Authors
2
Name
Order
Citations
PageRank
Blesson Varghese135235.03
Andrew Rau-chaplin263861.65