Misclassifications in financial risk tolerance

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.

Keywords:

• risk perception
• decision-making
• emotion recognition
• classification methods
• Iowa Gambling Task
• skin conductance response

Subject JEL Classification Codes:

• D81
• C91
• C38

Acknowledgements

This research was supported by a grant from the Italian Ministry of University and Research as ‘Research of National Interest’ – PRIN 2007 (September 2008–September 2010). We thank CONSOB (Italian Securities and Exchange Commission) for valuable comments and observations.

Notes

1. We deliberately avoid traditional measures of individual risk aversion because, as Bechara and Damasio point out (2005, 337), economic models of expected utility state that ‘people established their values of wealth on the basis of the pain and pleasure that it would give them’, but these models practically neglect the role of emotion in human decisions, and are absolutely ‘inconsistent with their foundations’.

2. The confusion matrix is a mathematical instrument that allows one to describe a classification model showing correct and incorrect classifications: the ‘closer’ the confusion matrix to a diagonal matrix, the better the performance of the associated classification model.

3. The ROC curve is a graph showing a true positive rate on the vertical axis and a false positive rate on the horizontal axis, as the classification threshold t varies.

4. We are confident that results do not depend on the kind of PDFRT questionnaire used.