Paper: arXiv 2408.15675

Authors: E. Ruben van Beesten

Abstract

I propose a functional on the space of spectral risk measures that quantifies their degree of risk aversion''. This quantification formalizes the idea that some risk measures are more risk-averse’’ than others. I construct the functional using two axioms: a normalization on the space of CVaRs and a linearity axiom. I present two formulas for the functional and discuss several properties and interpretations.

Complexity vs Empirical Score

  • Math Complexity: 8.0/10
  • Empirical Rigor: 1.0/10
  • Quadrant: Lab Rats — theoretically deep, empirically untested

Why this score: This paper presents a rigorous theoretical and axiomatic framework for quantifying the degree of risk aversion in spectral risk measures, filling a significant theoretical gap. However, it is purely mathematical with no empirical backtesting or real-world data analysis included in the excerpt.

Research Flowchart

  flowchart TD
    A[Goal: Quantify Degree of Risk Aversion for Spectral Risk Measures] --> B[Input: Space of Spectral Risk Measures & CVaR]
    B --> C[Establish Axiomatic Framework: Normalization & Linearity]
    C --> D[Derive Functional Formulas & Computational Representations]
    D --> E[Outcome: Formalized Comparison of Risk-Averse Measures & Properties]

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2 of 467 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.