Pricing real options based on linear loss functions and conditional value at risk

Kyongsun Kim and Chan S. Park

The Engineering Economist, 2020, vol. 66, issue 1, 3-26

Abstract: The main purpose of this paper is to expand real option analysis out of the realm of pure financial option pricing techniques. To overcome many of the well-known concerns by adopting the financial option pricing techniques for modeling real options problems such as replicating portfolio concept, geometric Brownian motion as underlying stochastic process, and estimating project volatility, we propose an alternative real option valuation based on the loss function approach. The option value determined by the loss function approach is equivalent to the expected value of perfect information (EVPI) in decision analysis. It basically sets the upper bound of risk premium to pay in retaining the options. In practice, many firms utilize the concept of Value at Risk to manage their portfolio risk. If a firm sets a target VAR, then we may be able to link this VAR in refining the actual risk premium to pay in hedging the risk embedded in the investment. With this practice in mind, we present a logic to figure out an appropriate amount of real option premium to pay for a given level of risk tolerance. A comprehensive example is presented to demonstrate the computational procedures as well as economic interpretations on the outcomes.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/0013791X.2020.1867273 (text/html)
Access to full text is restricted to subscribers.

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:taf:uteexx:v:66:y:2020:i:1:p:3-26

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UTEE20

DOI: 10.1080/0013791X.2020.1867273

Access Statistics for this article

The Engineering Economist is currently edited by Sarah Ryan

More articles in The Engineering Economist from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().