Arbeitspapier

Sensitivity-implied tail-correlation matrices

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.

Language
Englisch

Bibliographic citation
Series: ICIR Working Paper Series ; No. 33/19

Classification
Wirtschaft
Insurance; Insurance Companies; Actuarial Studies
Financial Institutions and Services: Government Policy and Regulation
Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
Subject
Risk aggregation
Capital allocation
Portfolio optimization

Event
Geistige Schöpfung
(who)
Paulusch, Joachim
Schlütter, Sebastian
Event
Veröffentlichung
(who)
Goethe University Frankfurt, International Center for Insurance Regulation (ICIR)
(where)
Frankfurt a. M.
(when)
2021

Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Paulusch, Joachim
  • Schlütter, Sebastian
  • Goethe University Frankfurt, International Center for Insurance Regulation (ICIR)

Time of origin

  • 2021

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