Haezendonck-Goovaerts Capital Allocation Rules

42 Pages Posted: 3 Sep 2020

See all articles by Gabriele Canna

Gabriele Canna

University of Milano-Bicocca, Department of Statistics and Quantitative Methods

Francesca Centrone

Università del Piemonte Orientale - Dipartimento di Studi per l'Economia e l'Impresa

Emanuela Rosazza Gianin

University of Milano-Bicocca - Dip. di Statistica e Metodi Quantitativi

Date Written: July 25, 2020

Abstract

This paper deals with the problem of capital allocation for a peculiar class of risk measures, namely the Haezendonck-Goovaerts (HG) ones. We generalize the capital allocation rule (CAR) introduced by Xun et al. for Orlicz risk premia, using firstly an approach based on Orlicz quantiles and secondly a more general one based on the, here introduced, concept of linking functions. Further on, we use the same construction of to extend the CARs previously introduced to HG risk measures. We therefore study the properties of different CARs for HG risk measures, both in the quantile-based setting and in the linking one. Finally, we provide robust versions of the introduced CARs, both considering the case of ambiguity over the probabilistic model and the one of multiple Young functions, following the scheme of.

Keywords: Capital Allocation, Haezendonck-Goovaerts Risk Measures, Orlicz Risk Premium, Quantiles, Ambiguity.

JEL Classification: G32

Suggested Citation

Canna, Gabriele and Centrone, Francesca and Rosazza Gianin, Emanuela, Haezendonck-Goovaerts Capital Allocation Rules (July 25, 2020). Available at SSRN: https://ssrn.com/abstract=3660385 or http://dx.doi.org/10.2139/ssrn.3660385

Gabriele Canna

University of Milano-Bicocca, Department of Statistics and Quantitative Methods ( email )

Via Bicocca degli Arcimboldi 8
Milano, Milano 20126
Italy

Francesca Centrone (Contact Author)

Università del Piemonte Orientale - Dipartimento di Studi per l'Economia e l'Impresa ( email )

Via Perrone 18
Novara, 28100
Italy

Emanuela Rosazza Gianin

University of Milano-Bicocca - Dip. di Statistica e Metodi Quantitativi ( email )

Milan
Italy

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