Policy-Constrained Valuation of Real Options Using Monte Carlo Simulation: The Role of the Exercise Condition
Purpose: This paper investigates how the economic value of managerial flexibility depends on the design of the decision rule governing option execution. It distinguishes between the policy-constrained real option value (ROV), representing the expected, non-negative potential of flexibility and the financial outcome of managerial flexibility (FOMF), which captures the realised economic effect of managerial actions that may be either positive or negative. The study aims to assess how the choice of the decision variable (EBIT, unit margin, FCFE, or sales volume) and the critical threshold (trigger value) influence both ROV and FOMF under conditions of risk and uncertainty. Design/Methodology/Approach: A simulation-based valuation framework is developed and applied to a theoretical manufacturing investment project located in the European Union. Two complementary valuation models are used: (1) the Double Monte Carlo (2MC) procedure, which estimates the realised financial outcome (FOMF) by comparing base and extended project NPVs across 100,000 stochastic iterations; and (2) the Simulation-based Comparative Valuation (SCV) framework, which estimates the policy-constrained real option value (ROV) by truncating negative outcomes to zero. Both approaches are embedded in a discounted cash flow (NPV) model that includes stochastic drivers (unit margin and demand volume), consistent financing assumptions, and rule-based execution logic. Findings: The results indicate that the expansion flexibility, under the assumed risk structure and decision rules, does not generate positive realised value: FOMF remains negative for all tested variables and trigger thresholds, while ROV stays non-negative and peaks at 89.4 thousand EUR for an EBIT trigger of 200 thousand EUR. The analysis demonstrates that option value depends critically on the choice of trigger variable and the definition of the execution condition. Stricter decision rules reduce both ROV and FOMF despite lowering the share of erroneous exercises. The value of flexibility is maximised when exercised frequently, even at the expense of higher error probability. None of the analysed decision variables yields a positive expected FOMF, confirming that the designed flexibility lacks economic justification under current assumptions. Practical Implications: For managers, the study highlights that purchasing flexibility, such as additional land for potential expansion may increase project risk, without improving expected returns unless the trigger condition is well-calibrated. Decision rules should be operationally clear, empirically tested, and defined during the design stage of flexibility creation rather than ex post. Originality/Value: The paper introduces a dual-metric, policy-constrained simulation framework that bridges theoretical real option valuation and practical decision-making. By jointly using ROV and FOMF, it differentiates potential from realised value and offers diagnostic tools, execution frequency, zero-mass share, timing that improve managerial interpretation of investment flexibility.