Decomposable sums and their implications on naturally quasiconvex risk measures

TL;DR

This paper explores the concept of natural quasiconvexity in risk measures, relating it to decomposable sums and convexity indices, and establishes conditions under which these properties are equivalent in certain function spaces.

Contribution

It provides a detailed analysis of natural quasiconvexity, extending the convexity index to topological vector spaces, and shows equivalence with convexity for conditional risk measures on L^p spaces.

Findings

Natural quasiconvexity is related to additively decomposable sums.

Convexity and natural quasiconvexity are equivalent in L^p spaces under certain conditions.

Introduces a generalized convexity index in topological vector spaces.

Abstract

Convexity and quasiconvexity are two properties that capture the concept of diversification for risk measures. Between the two, there is natural quasiconvexity, an old but not so well-known property weaker than convexity but stronger than quasiconvexity. A detailed discussion on natural quasiconvexity is still missing and this paper aims to fill this gap in the setting of conditional risk measures. We relate natural quasiconvexity to additively decomposable sums. The notion of convexity index, defined in 1980s for finite-dimensional vector spaces, plays a crucial role in the discussion of decomposable sums. We propose a general treatment of convexity index in topological vector spaces and use it to study naturally quasiconvex risk measures. We prove that natural quasiconvexity and convexity are equivalent for conditional risk measures on $L^p$ spaces, $p \geq 1$, under mild continuity and locality conditions. Finally, we discuss an alternative notion of locality with respect to an orthonormal basis in $L^2$.