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dc.contributor.authorNkwe, Hlompho K.
dc.date.accessioned2022-04-20T13:49:45Z
dc.date.available2022-04-20T13:49:45Z
dc.date.issued2019-12-10
dc.identifier.urihttp://hdl.handle.net/10311/2393
dc.descriptionA dissertation submitted to the Dept. of Mathematics, Faculty of Science, University of Botswana in partial fulfillment of the requirement of the degree of Masters in Mathematics. Citation: Nkwe, H.K. (2019) Capital budgeting under uncertainty: and option to invest, University of Botswana.en_US
dc.description.abstractUncertainty and irreversibility of capital expenditures are major concerns in capital budgeting. In a highly uncertain world were management has the flexibility to adjust their operating strategy, option value is created, this option value is not captured by standard methods of capital budgeting. In this paper we review standard methods of capital budgeting such as discounted cash- flow (DCF), return on investment (ROI), payback period. Complex methods such as Monte-Carlo simulation and scenario analysis are discussed. We then look at decision tree analysis (DTA) and how it addresses the issue of flexibility and it's main shortcoming i.e. `the discount rate problem'. Real options analysis (ROA) is discussed and we look at how it addresses the issue of managerial flexibility and how it overcomes the discount rate problem inherent in DTA. ROA is then applied to value an investment opportunity of a basalt quarry by Mbebane Enterprises. The project according to NPV analysis and IRR method found it to be a `go' project. Using ROA, the CRR model in particular, we found option value to be signicantly larger than the NPV. The binomial lattice was used as a guiding tool for timing the investment.en_US
dc.language.isoenen_US
dc.publisherUniversity of Botswana, www.ub.bwen_US
dc.subjectCapital budgetingen_US
dc.subjectcapital expendituresen_US
dc.subjectmanagementen_US
dc.subjectdiscounted cash-flowen_US
dc.subjectreturn on investmenten_US
dc.titleCapital budgeting under uncertainty: and option to investen_US
dc.typeMasters Thesis/Dissertationen_US
dc.linkUnpublisheden_US


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