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Correlation scenarios and correlation stress testing

Natalie Packham and Fabian Woebbeking

No 2021-012, IRTG 1792 Discussion Papers from Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series"

Abstract: We develop a general approach for stress testing correlations of financial asset portfolios. The correlation matrix of asset returns is specified in a parametric form, where correlations are represented as a function of risk factors, such as country and industry factors. A sparse factor structure linking assets and risk factors is built using Bayesian variable selection methods. Regular calibration yields a joint distribution of economically meaningful stress scenarios of the factors. As such, the method also lends itself as a reverse stress testing framework: using the Mahalanobis distance or highest density regions (HDR) on the joint risk factor distribution allows to infer worst-case correlation scenarios. We give examples of stress tests on a large portfolio of European and North American stocks.

Keywords: Correlation stress testing; reverse stress testing; factor selection; scenario selection; Bayesian variable selection; market risk management (search for similar items in EconPapers)
JEL-codes: G11 G32 (search for similar items in EconPapers)
Date: 2021
New Economics Papers: this item is included in nep-isf and nep-rmg
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