Ranking Metrics: Extending Acceptability and Performance Indexes

Fuente: arXiv
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Autori principali: Hitaj, Asmerilda, Mastrogiacomo, Elisa, Peri, Ilaria, Righi, Marcelo
Natura: Preprint
Pubblicazione: 2026
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author Hitaj, Asmerilda
Mastrogiacomo, Elisa
Peri, Ilaria
Righi, Marcelo
author_facet Hitaj, Asmerilda
Mastrogiacomo, Elisa
Peri, Ilaria
Righi, Marcelo
contents This paper develops an axiomatic framework for ranking metrics, a general class of functionals for evaluating and ordering financial or insurance positions. Unlike traditional risk-adjusted performance measures-such as the Sharpe ratio, RAROC, or Omega-that express reward per unit of risk, ranking metrics assign each position a performance level rather than a normalized return. Relying on monotonicity and a new property called cash-quasiconcavity, we derive representation results linking ranking metrics to families of acceptance sets and risk measures, extending the theory of acceptability indices. Classical ratios arise as special cases, while new examples-based on expected-loss, Lambda-quantile, and bibliometric indices-illustrate the framework's flexibility. Empirical applications to portfolio ranking and climate-risk insurance demonstrate its practical relevance.
format Preprint
id arxiv_https___arxiv_org_abs_2604_16438
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Ranking Metrics: Extending Acceptability and Performance Indexes
Hitaj, Asmerilda
Mastrogiacomo, Elisa
Peri, Ilaria
Righi, Marcelo
Risk Management
Probability
Mathematical Finance
This paper develops an axiomatic framework for ranking metrics, a general class of functionals for evaluating and ordering financial or insurance positions. Unlike traditional risk-adjusted performance measures-such as the Sharpe ratio, RAROC, or Omega-that express reward per unit of risk, ranking metrics assign each position a performance level rather than a normalized return. Relying on monotonicity and a new property called cash-quasiconcavity, we derive representation results linking ranking metrics to families of acceptance sets and risk measures, extending the theory of acceptability indices. Classical ratios arise as special cases, while new examples-based on expected-loss, Lambda-quantile, and bibliometric indices-illustrate the framework's flexibility. Empirical applications to portfolio ranking and climate-risk insurance demonstrate its practical relevance.
title Ranking Metrics: Extending Acceptability and Performance Indexes
topic Risk Management
Probability
Mathematical Finance
url https://arxiv.org/abs/2604.16438