Enhancing Spectrum License Valuation With Probabilistic Net Present Value Analysis

This paper proposes a probabilistic methodology for valuing spectrum licenses based on Net Present Value (NPV). Unlike traditional approaches that rely on deterministic forecasts, the proposed method treats the NPV as a random variable, allowing the derivation of a probability density function (PDF) using forecasting models, sensitivity analysis, and Monte Carlo simulations. This probabilistic framework accounts for uncertainties in key variables such as revenue, user growth, and network costs, and provides a more comprehensive and realistic assessment of investment viability. A structured methodology is introduced, involving network modeling, variable selection via Sobol analysis, time-series forecasting, and probabilistic simulation of future cash flows. The resulting PDF for NPV supports more informed decision-making for both regulators and operators by quantifying investment risks and enabling confidence-based pricing strategies. A simulation illustrates the application of the methodology and demonstrates how regulators can define license pricing criteria based on probabilistic thresholds. The results highlight the advantages of probabilistic over scenario-based NPV analysis, offering greater flexibility and insight into risk.