Electricity price modeling and asset valuation: a multi-fuel structural approach

Carmona, René, Coulon, Michael and Schwarz, Daniel (2013) Electricity price modeling and asset valuation: a multi-fuel structural approach. Mathematics and Financial Economics, 7 (2). pp. 167-202. ISSN 1862-9679

[img]
Preview
PDF - Accepted Version
Download (543kB) | Preview

Abstract

We introduce a new and highly tractable structural model for spot and derivative prices in electricity markets. Using a stochastic model of the bid stack, we translate the demand for power and the prices of generating fuels into electricity spot prices. The stack structure allows for a range of generator efficiencies per fuel type and for the possibility of future changes in the merit order of the fuels. The derived spot price process captures important stylized facts of historical electricity prices, including both spikes and the complex dependence upon its underlying supply and demand drivers. Furthermore, under mild and commonly used assumptions on the distributions of the input factors, we obtain closed-form formulae for electricity forward contracts and for spark and dark spread options. As merit order dynamics and fuel forward prices are embedded into the model, we capture a much richer and more realistic dependence structure than can be achieved by classical reduced-form models. We illustrate these advantages by comparing with Margrabe’s formula and a simple cointegration model, and highlight important implications for the valuation of power plants.

Item Type: Article
Schools and Departments: School of Business, Management and Economics > Business and Management
Subjects: H Social Sciences > HD Industries. Land use. Labour > HD9000 Special industries and trades > HD9502 Energy industries. Energy policy. Fuel trade
H Social Sciences > HG Finance
Q Science > QA Mathematics > QA0273 Probabilities. Mathematical statistics
T Technology > T Technology (General) > T0055.4 Industrial engineering. Management engineering > T0057 Applied mathematics. Quantitative methods
Depositing User: Michael Coulon
Date Deposited: 19 Jul 2013 13:30
Last Modified: 06 Mar 2017 06:42
URI: http://sro.sussex.ac.uk/id/eprint/45721

View download statistics for this item

📧 Request an update