Locatelli, G orcid.org/0000-0001-9986-2249, Mancini, M and Lotti, G (2020) A simple-to-implement real options method for the energy sector. Energy, 197. 117226. ISSN 0360-5442
Abstract
Investment appraisal methods based on real options are gaining popularity in academia, while the adoption by practitioners is still infrequent. Having in mind practitioners, the method is designed to be: conceptually easy to understand, based on realistic hypotheses and data available, able to provide quantitative indications and strategic guidelines. The method is based on a systematic simulation of several scenarios generated according to exercise thresholds of relevant investment parameters. An exercise threshold gives to the investors the exercise right of taking some decision, for instance building a power plant. An exercise threshold is therefore a rule to decide whether to exercise or not a certain option on the basis of the values of one or more state variables. Consequently, the probability distribution of the Net Present Value (or analogous indicator) of the investment is a function of the state variables and the exercise threshold. Systematically changing the exercise thresholds allow to (A) establishing the “real option value” and (B) calculate relevant indications about when and on which type of plant to invest. The method is presented in detail and applied to a case study assessing the investment appraisal of: coal plant, gas plant, large nuclear reactor and small modular reactor.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 Elsevier Ltd. All rights reserved. This is an author produced version of a paper published in Energy. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Real options; Decision-making; Investment appraisal; SMR; Large reactors |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Civil Engineering (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 04 Mar 2020 13:30 |
Last Modified: | 26 Feb 2021 01:38 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.energy.2020.117226 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:157998 |
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