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Measuring Probabilistic Risk Attitudes

Author

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  • Arnaldo Nascimento

    (Brazilian Agency for Research and Innovation, Rio de Janeiro 22210-901, Brazil; and Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro 38097, Brazil)

  • Che Tat Ng

    (Department of Pure Mathematics, University of Waterloo, Waterloo, Ontario N2L3G1, Canada)

  • Richard Gonzalez

    (Department of Psychology, University of Michigan, Ann Arbor, Michigan 48109)

Abstract

We introduce formal measures for two psychological factors of probabilistic risk attitudes: attractiveness (motivational factor) and discriminability (cognitive factor). Unlike previous approaches that relied on heuristic proxies, our measures precisely capture these two fundamental factors. Our measures are mathematically tractable, robust to discontinuities, such as in the NEO-additive case, and flexible to be applied to any weighting function, as well as to both small and large probabilities. Additionally, through detailed numerical analysis, we examine to what extent existing weighting function parameters capture the two factors: attractiveness and discriminability. Finally, using these new measures, we provide a formal understanding of the independence between motivational and cognitive factors.

Suggested Citation

  • Arnaldo Nascimento & Che Tat Ng & Richard Gonzalez, 2026. "Measuring Probabilistic Risk Attitudes," Management Science, INFORMS, vol. 72(6), pages 4780-4790, June.
    • Handle: RePEc:inm:ormnsc:v:72:y:2026:i:6:p:4780-4790
    DOI: 10.1287/mnsc.2024.04870
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