Project Valuation With Time-Varying Cash Flows: A Bayesian Approach

This article investigates the valuation of a project when the distributions of cash flows vary over time. The decision maker is assumed to be a Bayesian decision maker under uncertainty. Using the dynamic programming principle of backward induction and assuming that the capital asset pricing model is valid in each time period, we derive the project's valuation formulas and systematic risks, and investigate their characteristics. Our valuation formulas embed a Bayesian learning effect and differ from the traditional textbook capital budgeting formulas.