Abstract
In this paper we show the applicability of the Least Squares Monte Carlo (LSM) in valuing R&D investment opportunities. As it is well known, R&D projects are made in a phased manner, with the commencement of subsequent phase being dependent on the successful completion of the preceding phase. This is known as a sequential investment and therefore R&D projects can be considered as compound options. Moreover, R&D investments often involve considerable cost uncertainty so that they can be viewed as an exchange option, i.e. a swap of an uncertain investment cost for an uncertain gross project value. In this context, the LSM method is a powerful and flexible tool for capital budgeting decisions and for valuing R&D investments. In fact, this method provides an efficient technique to value complex real investments involving a set of interacting American-type options.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Abramowitz, M., Stegun, I.A.: Handbook of Mathematical Functions. Dover Pubblications, New York (1970)
Andergassen, R., Sereno, L.: Valuation of N-stage Investments Under Jump-Diffusion Processes. Computational Economics 39(3), 289–313 (2012)
Areal, N., Rodrigues, A., Armada, M.J.R.: Improvements to the Least Squares Monte Carlo Option Valuation Method. Review of Derivative Research 11(1–2), 119–151 (2008)
Black, F., Scholes, M.: The Pricing of Options and Corporate Liabilities. Journal of Political Economy 81, 637–659 (1973)
Carr, P.: The Valuation of American Exchange Options with Application to Real Options. In: Trigeorgis, L. (eds) Real Options in Capital Investment: Models, Stratigies and Applications. Praeger, Westport Connecticut, London (1995)
Cassimon, D., Engelen, P.J., Thomassen, L., Van Wouwe, M.: The valuation of a NDA using a 6-fold compound option. Research Policy 33(1), 41–51 (2004)
Cortelezzi, F., Villani, G.: Valuation of R&D sequential exchange options using Monte Carlo approach. Computational Economics 33(3), 209–236 (2009)
Hartmann, M., Hassan, A.: Application of real options analysis for pharmaceutical R&D project valuation-Empirical results from a survey. Research Policy 35(3), 343–354 (2006)
Lee, J., Paxson, D.A.: Valuation of R&D real American sequential exchange option. R&D Management 31(2), 191–201 (2001)
Longstaff, F.A., Schwartz, E.S.: Valuing American options by simulation: a simple least-squares approach. The Review of Financial Studies 14(1), 113–147 (2001)
Moreno, M., Navas, J.F.: On the Robustness of Least-Squares Monte Carlo (LSM) for Pricing American Derivatives. Review of Derivative Research 6(2), 107–128 (2003)
Myers, S.C.: Determinants of corporate borrowing. Journal of Financial Economics 5(2), 147–175 (1977)
Thomke, S.H.: The role of flexibility in the development of a new products: An empirical study. Research Policy 26(1), 105–119 (1997)
Villani, G.: Generalization of stratified variance reduction methods for monte carlo exchange options pricing. In: Perna Cira e Marilena Sibillo (eds.) Mathematical and Statistical Methods for Actuarial Sciences and Finance, pp. 379–387. Springer (2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Villani, G. (2014). Valuation of R&D Investment Opportunities Using the Least-Squares Monte Carlo Method. In: Corazza, M., Pizzi, C. (eds) Mathematical and Statistical Methods for Actuarial Sciences and Finance. Springer, Cham. https://doi.org/10.1007/978-3-319-02499-8_26
Download citation
DOI: https://doi.org/10.1007/978-3-319-02499-8_26
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02498-1
Online ISBN: 978-3-319-02499-8
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)