CEO overconfidence: Towards a new measure

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 li...

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Bibliographic Details
Published in:International review of financial analysis 2022-11, Vol.84, p.102367, Article 102367
Main Authors: Hatoum, Khalil, Moussu, Christophe, Gillet, Roland
Format: Article
Language:English
Subjects:
Bayesian networks
CEO overconfidence
Conditional probabilities
Corporate investments
Quantitative Finance
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Summary: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. •Bayesian network theory is used to construct a probability-based measure for CEO overconfidence based on several CEO- and firm-specific determinants of CEO overconfidence.•Probability of CEO overconfidence helps measure the frequency of overconfidence for CEOs•Probability 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.
ISSN:1057-5219
1873-8079
DOI:10.1016/j.irfa.2022.102367