REAL OPTIONS VALUATION AND ITS RELATIONSHIP TO BAYESIAN DECISION-MAKING METHODS

ABSTRACT It is well accepted that conventional NPV criterion fails to capture investment flexibility, and the market approach using riskless-arbitrage-pricing is ideally suited to price real options. However, when valuing complex real options, it is difficult to satisfy the restrictive assumptions required for risk-free arbitrage pricing. Using two-action linear payoff analysis, we show that when it is possible to delay and obtain additional information, an irreversible capital investment decision should be valued as an option taking into considering the value of flexibility. This option value is not based on risk-less arbitrage, but on a more fundamental concept in decision theory - the opportunity loss criterion. Our approach relates to the Quasi-Option concept of Arrow and Fisher (1974) and Henry (1974) that considers the value of gaining more information before making irreversible environment decisions. Lund (1991) provides an excellent analysis of the relationship between the Arrow and Fisher's [1] Quasi-Option Value and Black and Schole's Market based Model [4], and suggests using both ideas for valuing real options. Conrad (1980), Fisher and Hanemann (1987) and Hanemann (1989) discuss the relationship between Quasi-Option Value and Expected Value of Perfect Information (EVPI) with respect to environmental decisions. We extend the opportunity loss concept to value real options and analyze its relationship to EVPL We show that the value of a quasi-real option is equal to value of information. In the special case where a lognormal terminal distribution is assumed, we show that the EVPI is equivalent to the Black and Scholes model. We demonstrate how EVPI can be used to make investment decisions under uncertainty within an options framework. The suggested approach allows revision of option values sequentially using Bayesian methods at each decision point within the well-known decision theory framework. Financial economists have not considered the intersection between Bayesian decision framework and value of investment flexibility, that allow for a less restrictive set of assumptions.

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