Abstract
Correlation stress testing is motivated by a well-known phenomenon: correlations change under financial crises. The adjustment of correlation matrices may be required to evaluate the potential impact of these changes. Very often, some correlations are explicitly adjusted (core correlations), with the remainder left unspecified (peripheral correlations), although it would be more natural for both core correlations and peripheral correlations to vary. However, most existing methods ignore the potential change in peripheral correlations. In this paper, we propose a Black–Litterman approach to correlation stress testing in which the stress impact on the core correlations is transmitted to the peripheral correlations through the dependence structure of the empirical correlations. Copyright © 2014 Copyright Taylor & Francis Group, LLC.
Original language | English |
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Pages (from-to) | 1643-1649 |
Journal | Quantitative Finance |
Volume | 14 |
Issue number | 9 |
Early online date | Nov 2013 |
DOIs | |
Publication status | Published - 2014 |
Citation
Ng, F. C., Li, W. K., & Yu, P. L. H. (2014). A Black–Litterman approach to correlation stress testing. Quantitative Finance, 14(9), 1643-1649. doi: 10.1080/14697688.2013.843022Keywords
- Correlation stress testing
- Scenario test
- Black–Litterman
- Mahalanobis distance