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Using Improved Jump-Diffusion Modeling for Valuing R&D Investment

Abstract— The research and development (R&D) investment has a high degree of uncertainty and inherent asymmetry between gains and losses which have been concerned by enterprise executives for a long time. The uncertainties include technological uncertainty, cost uncertainty, market requirement uncertainty, future profit uncertainty and competitors' preemptive moves, etc. All these features have an impact on enterprise's willingness to adopt and make conventional investment approaches have not be very effective in R&D investment because they lack of flexibility. In this paper, we introduce learning parameters to jump-diffusion model for describing enterprises' mutual learning behaviors in investment process. Therefore, enterprises can acquire new information from pre-investment decisions of other competitors in market and capture cost and benefit flows variations under multiple uncertainties. The results support the fullest assessment of our approach in this research. Then, we also report on several extensions that demonstrate how the uncertainties affect enterprise R&D investment threshold.

Index Terms— R&D, Uncertainties, Jump-diffusion process, Learning parameter, Investment threshold

Shuo Zhang, Yiping Yang, Zhuang Wu
Dept. of Information, Capital University of Economics and Business, CHINA

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Cite: Shuo Zhang, Yiping Yang, Zhuang Wu, "Using Improved Jump-Diffusion Modeling for Valuing R&D Investment," Proceedings of 2017 the 7th International Workshop on Computer Science and Engineering, pp. 344-348, Beijing, 25-27 June, 2017.