Valuation of Contractual Assets Using Statistical Simulation

This paper develops a dynamic option-based model for the valuation of rental and other similarly structured lease contracts under the conditions of uncertainty that is then solved by statistical simulation (Monte Carlo). The motivation, research background and methodology of the paper follow up on a previously published general firm-theoretical approach by the author, who takes an interdisciplinary approach to apply the model in this particular context. It is shown that due to the path dependency of the problem, Monte Carlo is an appropriate and practical tool for analyzing embedded options, incident in most rental and lease relationships, and can be used as a major determinant of their value. In addition to its basic valuation function, exploitable for business acquisition or lease contracting purposes, this Monte Carlo model is very well disposed for various microeconomic analyses. Accordingly, we demonstrate the particular impacts and sensitivities of contractual party-specific, as well as environmental, factors including parties' transaction costs, information asymmetry and enforceability of legal claims