 A factor-model approach for correlation scenarios and correlation stress-testingNatalie Packham and Fabian Woebbeking No 2018-034, IRTG 1792 Discussion Papers from Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series" Abstract: In 2012, JPMorgan accumulated a USD 6.2 billion loss on a credit derivatives portfolio, the so-called "London Whale", partly as a consequence of de-correlations of non-perfectly correlated positions that were supposed to hedge each other. Motivated by this case, we devise a factor model for correlations that allows for scenario-based stress-testing of correlations. We derive a number of analytical results related to a portfolio of homogeneous assets. Using the concept of Mahalanobis distance, we show how to identify adverse scenarios of correlation risk. As an example, we apply the factor-model approach to the "London Whale" portfolio and determine the value-at-risk impact from correlation changes. Since our ndings are particularly relevant for large portfolios, where even small correlation changes can have a large impact, a further application would be to stress-test portfolios of central counterparties, which are of systemically relevant size. Keywords: Correlation stress testing; scenario selection; market risk; "London Whale" (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:zbw:irtgdp:2018034 Access Statistics for this paper More papers in IRTG 1792 Discussion Papers from Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series" Contact information at EDIRC. |
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