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Real options valuation of a power generation project : a Monte Carlo approach
In today's economic environment characterised by change, uncertainty, and the need for flexibility, it is becoming important for decision makers to account for both uncertainty and the companys ability to react to new information. Real options has emerged as an approach that addresses this challenge...
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| Format: | Thesis |
| Language: | English |
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Department of Mathematics and Applied Mathematics
2024
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| Summary: | In today's economic environment characterised by change, uncertainty, and the need for flexibility, it is becoming important for decision makers to account for both uncertainty and the companys ability to react to new information. Real options has emerged as an approach that addresses this challenge by drawing parallels between the real economy and the use and valuation of financial options. Monte Carlo simulation is a powerful technique for option valuation, but because of its forward looking nature is normally applied when early exercise is not allowed. In the real economy, this would be limiting because flexibilities that exist are not normally constrained to particular exercise dates. The Least-Squares Monte Carlo (LSM) is an approach that allows for the valuation of options where early exercise is possible. In this thesis, we present an implementation of the LSM approach to the Real Options valuation of a project that involves the investment in a new open cycle (OCGT) gas power generation plant, used to supply peak electricity demand in an open electricity wholesale market. The embedded flexibilities that are considered are the option to expand, and the option to abandon the project. The uncertainties that the project is exposed to include: the cost of fuel, the price at which electricity is sold and the quantity of electricity sold each year. We show that the LSM approach offers several benefits for the valuation of such projects with complex payoff functions. |
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