An Impossibility Theorem on Capital Allocation

Scandinavian Actuarial Journal, forthcoming

18 Pages Posted: 18 Nov 2021 Last revised: 24 Jun 2022

See all articles by Yuanying Guan

Yuanying Guan

DePaul University - Department of Mathematical Sciences

Andreas Tsanakas

Bayes Business School (formerly Cass), City, University of London

Ruodu Wang

University of Waterloo - Department of Statistics and Actuarial Science

Date Written: November 16, 2021

Abstract

Two natural and potentially desirable properties for capital allocation rules are top-down
consistency and shrinking independence. Top-down consistency means that the total capital is
determined by the aggregate portfolio risk. Shrinking independence means that the risk capital
allocated to a given business line should not be affected by a proportional reduction of exposure
in another business line. These two properties are satis ed by, respectively, the Euler allocation
rule and the stress allocation rule. We prove an impossibility theorem which states that these two
properties jointly lead to the trivial capital allocation based on the mean. When a subadditive
risk measure is used, the same result holds for weaker versions of shrinking independence, which
prevents the increase in risk capital in one line, when exposure to another is reduced. The
impossibility theorem remains valid even if one assumes strong positive dependence among the
risk vectors.

Keywords: Euler allocation, stress scenarios, top-down consistency, shrinking independence

JEL Classification: C70

Suggested Citation

Guan, Yuanying and Tsanakas, Andreas and Wang, Ruodu, An Impossibility Theorem on Capital Allocation (November 16, 2021). Scandinavian Actuarial Journal, forthcoming, Available at SSRN: https://ssrn.com/abstract=3964775 or http://dx.doi.org/10.2139/ssrn.3964775

Yuanying Guan

DePaul University - Department of Mathematical Sciences ( email )

Chicago, IL 60604
United States

Andreas Tsanakas

Bayes Business School (formerly Cass), City, University of London ( email )

106 Bunhill Row
London, EC1Y 8TZ
United Kingdom

Ruodu Wang (Contact Author)

University of Waterloo - Department of Statistics and Actuarial Science ( email )

Waterloo, Ontario N2L 3G1
Canada

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