CEO Overconfidence in Shaping Corporate Investments Decision Making.
Sous la direction de M. Roland Gillet (PRISM)
This research work aims at exploring the impact of CEO overconfidence on corporate investments by establishing an original theoretical model that can estimate potential losses in corporate investments’ value due to CEO overconfidence. The theoretical model incorporates a newly introduced variable in behavioral finance which is the “probability of CEO overconfidence”; this variable is used along other variables to establish the model.
Furthermore, Bayesian network theory is used to construct this 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, I 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.
An original review of behavioral finance has also been developed in line with this research objectives. The review scientifically identifies and selects a range of the most relevant articles in order to provide a consolidated view of relevant literature on CEO overconfidence and its effect on corporate investments. Literature in this area of research supports the existence of destructive effects on corporate investments due to CEO overconfidence.
Keywords: Corporate investments; CEO overconfidence; Decision making process; Conditional Probabilities; Bayesian networks; Literature review; Behavioral finance