Superiority of Monte Carlo simulation in valuing real options within public–private partnerships

Ales S. Berk () and Dejan Podhraski
Additional contact information
Ales S. Berk: FELU
Dejan Podhraski: Real Options Consulting Ltd

Risk Management, 2018, vol. 20, issue 1, No 1, 28 pages

Abstract: Abstract Monte Carlo simulation and geometric Brownian motion are the two methods employed for valuation of guarantees in public–private partnership projects. In this article we argue that any guarantee within the projects that exhibit non-constant growth rate of demand should always be evaluated using Monte Carlo simulation. Namely, we find that in a typical infrastructure project geometric Brownian motion underestimates cash flows and overestimates the value of the granted guarantee of public partner. In economic terms, our results imply more implemented projects, which are urgently needed, and thus a higher impact on economic well-being through better risks sharing mechanisms and project risk management. We also contribute to the literature by arguing that proper capture of the growth rate is much more important than the proper capture of volatility, already reported in the field.

Keywords: Public–private partnership; Real options; Infrastructure projects; Capital budgeting decisions; Guarantees; Monte Carlo simulation; Geometric Brownian motion (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1057/s41283-017-0025-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pal:risman:v:20:y:2018:i:1:d:10.1057_s41283-017-0025-9

Ordering information: This journal article can be ordered from
https://www.palgrave.com/gp/journal/41283

DOI: 10.1057/s41283-017-0025-9

Access Statistics for this article

Risk Management is currently edited by Igor Loncarski

More articles in Risk Management from Palgrave Macmillan
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().