On Geometrically Convex Risk Measures

التفاصيل البيبلوغرافية
العنوان: On Geometrically Convex Risk Measures
المؤلفون: Aygün, Mücahit, Bellini, Fabio, Laeven, Roger J. A.
سنة النشر: 2024
المجموعة: Mathematics
Quantitative Finance
مصطلحات موضوعية: Quantitative Finance - Risk Management, Mathematics - Probability, 91B06, 26A51, 52A41
الوصف: Geometrically convex functions constitute an interesting class of functions obtained by replacing the arithmetic mean with the geometric mean in the definition of convexity. As recently suggested, geometric convexity may be a sensible property for financial risk measures ([7,13,4]). We introduce a notion of GG-convex conjugate, parallel to the classical notion of convex conjugate introduced by Fenchel, and we discuss its properties. We show how GG-convex conjugation can be axiomatized in the spirit of the notion of general duality transforms introduced in [2,3]. We then move to the study of GG-convex risk measures, which are defined as GG-convex functionals defined on suitable spaces of random variables. We derive a general dual representation that extends analogous expressions presented in [4] under the additional assumptions of monotonicity and positive homogeneity. As a prominent example, we study the family of Orlicz risk measures. Finally, we introduce multiplicative versions of the convex and of the increasing convex order and discuss related consistency properties of law-invariant GG-convex risk measures.
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2403.06188
رقم الأكسشن: edsarx.2403.06188
قاعدة البيانات: arXiv