CEO overconfidence: Towards a new measure

Khalil Hatoum, Christophe Moussu and Roland Gillet

International Review of Financial Analysis, 2022, vol. 84, issue C

Abstract: Bayesian network theory is used to construct a novel probability-based measure for CEO overconfidence. This measure is estimated by studying the probabilistic correlation between CEO overconfidence and several CEO- and firm-specific determinants of overconfidence, that have been documented in the literature. Using S&P 500 firms over the period 2007–2017, we show that the established Bayesian network model has a high fitting and prediction accuracy of CEO overconfidence. This novel measure of CEO overconfidence can be used to conduct empirical studies in corporate and behavioral finance. It also provides a tool to improve decision-making in firms and corporate governance.

Keywords: CEO overconfidence; Conditional probabilities; Bayesian networks; Corporate investments (search for similar items in EconPapers)
JEL-codes: C11 G40 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:84:y:2022:i:c:s1057521922003179

DOI: 10.1016/j.irfa.2022.102367

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