Improving Capital Budgeting Through Probabilistic Approaches

Abstract

This article advocates the multiple benefits of applying probabilistic approaches to capital budgeting through enriching the deterministic framework with a stochastic modeling of main impacting inputs (including a methodology for selecting the most important inputs to be modeled stochastically). The essential limitations of the deterministic capital budgeting methodology are presented: behavioral biases (optimism, asymmetric probability distribution, etc.), incomplete view of the risk return profile, neglecting real options (be it to evaluate a project or to reshape it in a value creation perspective), portfolio diversification impact, etc. Through some selected examples, we illustrate how each of these limitations can be mitigated thanks to probabilistic approaches leading to a better decision-making process and ultimately more value creation.