Abstract: An overconfident newsvendor model is developed by defining the overconfidence as the newsvendor’s overprecision about the true demand. Closed-form optimal order quantity of the overconfident newsvendor is derived. A linear relationship between the optimal order quantity and that obtained from the benchmark newsvendor model is established. Then, the impact of overconfidence level on order bias and profit loss is analyzed. It is found that, as the overconfidence level increases, the overconfident newsvendor’s optimal order deviates far away from the benchmark newsvendor’s optimal order. Furthermore, the profit loss resulting from the overconfident is an increasingly convex function of the overconfidence level. Finally, a numerical example demonstrates the validity of the proposed model and results.