Valuation of Contractual Assets Using Statistical Simulation

Abstract

153This 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. IntroductionValue-based methods for assessing tangible investments are familiar tools for most decision-makers, constituting a fundamental part of management education and are extensively used for key components of the strategic management process, such as capital budgeting. The essential principles of the discounted cash-flow model have been in the public domain and in regular use by practitioners for at least the last one hundred years (Fischer, 1907;Rubinstein, 2006;Williams, 1938).More recently, many researchers have expressed that, besides tangible assets, the value of any business may be strongly determined by intangibles (Blair & Wallman, 2001;Daum, 2001;Lev, 2001;Saaty, 2009) These generally constitute various rights, opportunities and obligations that can substantially enhance and/or diminish the value of a company when compared to the balance of its assets and liabilities, and they may include diverse items, ranging from licenses and brands to specific business skills and market share (Corrado, Hulten, & Sichel, 2005;Kogut and Zander, 1992;Ortiz, 2006;Wang, Wang, & Liang, 2014

Valuing the Innovation Potential of New Materials

“…Zjištěný rozdíl ve prospěch střední čisté současné hodnoty výrobního zařízení zjištěné simulačním modelem lze interpretovat hodnotou flexibility substituce ve výrobě. Jedná se o jev, běžně označovaný jako reálná opce, přičemž parametrická statistická simulace je vhodnou metodou jeho oceňování 25,26 . Obecně lze říci, že hodnotu reálných opcí zvyšuje nejistota budoucího vývoje hodnoto-Obr.…”