ISBN: 978-981-11-3671-9 DOI: 10.18178/wcse.2017.06.059
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
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.