Humboldt-Universität zu Berlin - High Dimensional Nonstationary Time Series

IRTG1792DP2021 012

Correlation scenarios and correlation stress testing

Natalie Packham
Fabian Woebbeking

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.

Correlation stress testing, reverse stress testing, factor selection, scenario
selection, Bayesian variable selection, market risk management

JEL Classification:
G11, G32