Abstract
This paper provides an improved model, based on historical data, that describes the returns on assets that result from R&D efforts to assist managers of public and private R&D activities. Such a model may lead to better decision support tools to monetize the value that may be extracted from R&D, which is otherwise often undervalued. Real option pricing models are used to gauge appropriate funding levels for assets such as R&D projects that contain large time-dependent uncertainties. However, this study finds that assuming the Gaussian distribution describes fluctuations in value is not appropriate for assets whose value is derived from R&D activities. This conclusion is based on a study of 43 military R&D projects and 100 technology-intensive small firms. A power law, such as the Cauchy distribution, is shown to be more accurate in describing fluctuations in returns from R&D investments.
Original language | English |
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Pages (from-to) | 219-228 |
Number of pages | 10 |
Journal | Science and public policy |
Volume | 40 |
Issue number | 2 |
DOIs | |
Publication status | Published - 18 Dec 2013 |
Keywords
- Real options
- Black–Scholes
- Power law
- Thick tail
- Cauchy distribution
- n/a OA procedure