An Option-Based Operational Risk Management Model for Pandemics

In this paper we employ the theory of real option pricing to address problems in the area of operational risk management. We develop a two-stage model to help firms determine the optimal suspension-reactivation triggers in the events of pandemics. In the first stage, we propose a regime-dependent epidemic model to simulate the spread of the virus, depending on whether the firm is active or inactive. In the second stage, we view the reactivation decision as a call option and the suspension decision as a put option, and use dynamic programming methods to obtain the optimal switching thresholds. Our method can be regarded as a quantitative implementation of the CDC’s instructions for pandemic preparation. We find that when they take the uncertainty of disease transmission into consideration, firms are more conservative about the decisions of suspension and reactivation. We also find that when firms incur switching costs, the suspension threshold increases with costs, whereas the reactivation threshold decreases with costs. By adopting disease control policies, firms can increase their values in both regimes.