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QuPARA: Query-Driven Large-Scale Portfolio Aggregate Risk Analysis on MapReduce
Year Of Publication: 2013
Month Of Publication: August
Resource Link: Click here to open
Pages: 9
Download Count: 0
View Count: 1385
Comment Num: 0
Language: English
Source: working paper
Who Can Read: Free
Date: 8-23-2013
Publisher: Administrator
Summary
In this paper, we explore the design of a flexible framework for portfolio risk analysis that facilitates answering a rich variety of catastrophic risk queries. Rather than aggregating simulation data in order to produce a small set of high-level risk metrics efficiently (as is often done in production risk management systems), the focus here is on allowing the user to pose queries on unaggregated or partially aggregated data. We implemented a prototype system, called QuPARA (Query-Driven Large-Scale Portfolio Aggregate Risk Analysis), using Hadoop, which is Apache's implementation of the MapReduce paradigm. This allows the user to take advantage of large parallel compute servers in order to answer ad hoc risk analysis queries efficiently even on very large data sets typically encountered in practice. We describe the design and implementation of QuPARA and present experimental results that demonstrate its feasibility. A full portfolio risk analysis run consisting of a 1,000,000 trial simulation, with 1,000 events per trial, and 3,200 risk transfer contracts can be completed on a 16-node Hadoop cluster in just over 20 minutes.
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Author(s)
Rau-Chaplin, Andrew Sign in to follow this author
Varghese, Blesson Sign in to follow this author
Wilson, Duane Sign in to follow this author
Yao, Zhimin Sign in to follow this author
Zeh, Norbert Sign in to follow this author
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