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Misclassifications in financial risk tolerance

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  • Caterina Lucarelli
  • Pierpaolo Uberti
  • Gianni Brighetti

Abstract

This paper analyses the empirical risk tolerance of individuals and the role of physiological measures of risk perception. By using a test that mimics the financial decision process in a laboratory setting ( N =445), we obtained an ex-post empirical measure of individual risk tolerance. Predictive classification models allow us to evaluate the accuracy of two alternative risk-tolerance forecasting methods: a self-report questionnaire and a psycho-physiological experiment. We find that accuracy of self-assessments is low and that misclassifications resulting from questionnaires vary from 36 to 65%: individuals asked to self-evaluate their risk tolerance reveal a high probability of failing their judgement, i.e. they behave as risk takers, even if, before the task, they define themselves as risk averse (and vice versa). Conversely, when the risk-tolerance forecast is obtained from individuals' physiological arousal, observed via their somatic activation before risky choices, the rate of misclassification is considerably lower (~17%). Emotions are confirmed to influence the financial risk-taking process, enhancing the accuracy of the individual risk-tolerance forecasting activity. Self-report questionnaires, conversely, could lead to inadequate risk-tolerance assessments, with consequent unsuitable investment decisions. Bridging these results from the individual to the institutional level, our findings should enhance cautiousness, among regulators and financial institutions, on the (ab)use of risk tolerance questionnaires as tools for classifying individuals' behaviour under risk.

Suggested Citation

  • Caterina Lucarelli & Pierpaolo Uberti & Gianni Brighetti, 2015. "Misclassifications in financial risk tolerance," Journal of Risk Research, Taylor & Francis Journals, vol. 18(4), pages 467-482, April.
  • Handle: RePEc:taf:jriskr:v:18:y:2015:i:4:p:467-482
    DOI: 10.1080/13669877.2014.910678
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    Cited by:

    1. Muna Sharma & Swarn Chatterjee, 2021. "Cognitive Functioning: An Underlying Mechanism of Age and Gender Differences in Self-Assessed Risk Tolerance among an Aging Population," Sustainability, MDPI, vol. 13(4), pages 1-9, February.
    2. Kong, Hyeongwoo & Yun, Wonje & Kim, Woo Chang, 2023. "Tracking customer risk aversion," Finance Research Letters, Elsevier, vol. 54(C).
    3. Lackes, Richard & Siepermann, Markus & Vetter, Georg, 2020. "What drives decision makers to follow or ignore forecasting tools - A game based analysis," Journal of Business Research, Elsevier, vol. 106(C), pages 315-322.
    4. Sander, Julian, 2024. "The Role of Emotions in Investment Decisions: The Effects of Vividness of a Crowdfunding Campaign Video," Thesis Commons 6gptv, Center for Open Science.
    5. BĂ©atrice BOULU-RESHEF & Alexis DIRER & Nicole VON WILCZUR, 2022. "Algorithmic vs. Human Portfolio Choice," LEO Working Papers / DR LEO 2966, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.

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