TY  - JOUR
A1  - Paulusch, Joachim
A1  - Schlütter, Sebastian
T1  - Sensitivity-implied tail-correlation matrices
T2  - Journal of Banking & Finance
N2  - Tail-correlation matrices are an important tool for aggregating risk measurements across risk categories, asset classes and/or business segments. This paper demonstrates that traditional tail-correlation matrices—which are conventionally assumed to have ones on the diagonal—can lead to substantial biases of the aggregate risk measurement’s sensitivities with respect to risk exposures. Due to these biases, decision-makers receive an odd view of the effects of portfolio changes and may be unable to identify the optimal portfolio from a risk-return perspective. To overcome these issues, we introduce the “sensitivity-implied tail-correlation matrix”. The proposed tail-correlation matrix allows for a simple deterministic risk aggregation approach which reasonably approximates the true aggregate risk measurement according to the complete multivariate risk distribution. Numerical examples demonstrate that our approach is a better basis for portfolio optimization than the Value-at-Risk implied tail-correlation matrix, especially if the calibration portfolio (or current portfolio) deviates from the optimal portfolio.
KW  - Risk aggregation
KW  - Tail correlation
KW  - Portfolio optimization
Y1  - 2021
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/78532
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-785324
SN  - 0378-4266
VL  - 134.2022
IS  - 106333
PB  - Elsevier
CY  - Amsterdam
ER  -