Capturing the Option Value of R&D

This simple model for valuing R&D opportunities is based on cost and revenue projections routinely used to determine the NPh of investment alternatives. OVERVIEW: Real option models capture the value of flexibility in R&D projects. This value lies in the fact that management always has the option to abandon the project if the results of R&D are not promising, thus limiting losses to the amount invested in the R&D phase. Traditional net present value (NPV) analysis fails to recognize this flexibility and therefore tends to undervalue R&D opportunities. The Black-Scholes model has been used extensively for financial options, but may be difficult to apply to R&D projects. Instead, it is suggested that the cost and revenue cash flows associated with implementing a project be used to measure the option value of R&D. This model captures the uncertainty associated with cash flow projections while simplifying some of the assumptions and data required for the Black-Scholes model. The similarities between a stock option and R&D project have been recognized in the literature for several decades. Both options give the investor the opportunity to capitalize on future earnings while limiting the potential loss. Like stock options, an R&D project with a large variance in expected returns is more attractive than one with a small variance, given that both projects have equal average returns, because the project with the larger variance has the potential of a much larger payoff with no additional cost (if it fails, the loss is limited to the R&D investment). Unfortunately, traditional discounted cash flow analysis fails to recognize the value of this flexibility. The result is that R&D projects are undervalued and often rejected due to a negative net present value. Realizing that the option value of an R&D project should be captured when analyzing investment opportunities, several authors have suggested using option pricing theory to value R&D (1-3). The most widely accepted financial option model is the Black-Scholes model (4), and a number of authors have applied it to R&D projects (5-7. However, the assumptions required by these models may present practitioners with some difficult problems. For example, the Black-Scholes model assumes that the future value of the stock, or in the case of R&D the value of the cash flows received if the R&D results are implemented, is distributed lognormally and cannot be negative. This may not be the case with every R&D project. Trigeorgis (8,9) discussed the problem of determining the value of the underlying asset for a real option (a parameter required for the Black-Scholes model). Essentially, if the underlying asset is not traded in the market (as is the case for R&D projects), it is difficult, if not impossible, to establish this value. Finally, recognize that the volatility in the Black-Scholes models is derived from the "price relative" (final stock price divided by initial stock price) and obtained from historical data, which does not usually exist for R&D projects. Rather than using traditional financial options models, some authors have taken a decision analysis approach to the problem. For example, Morris, Teisberg and Kolbe described how projects with negative net present value have a positive value when the option to abandon is incorporated in the model (10). They illustrated this for projects whose net cash flows are normally distributed. Other authors have used similar approaches (11, 12). The advantage of this approach is that it eliminates the need to make some of the possibly unrealistic assumptions required by the Black-Scholes model. However, it still requires management to estimate the distribution of net cash flows. While this may be possible, it is more likely that management will have access to two separate estimates: production and marketing costs, and anticipated revenues. …