CALIBRATION OF MULTIFACTOR MODELS IN ELECTRICITY MARKETS

Martin Barlow (), Yuri Gusev () and Manpo Lai ()
Additional contact information
Martin Barlow: Department of Mathematics, University of British Columbia, Vancouver, Canada V6T 1Z2, Canada
Yuri Gusev: Pacific Institute for Mathematical Sciences, University of British Columbia, Vancouver, Canada V6T 1Z2, Canada
Manpo Lai: Algorithmics Inc., Toronto, Canada

International Journal of Theoretical and Applied Finance (IJTAF), 2004, vol. 07, issue 02, 101-120

Abstract: Spot prices of electricity and other energy commodities are often modeled by multifactor stochastic processes. This poses a problem of estimating models' parameters based on historical data, i.e. calibrating them to markets. Here we show how a traditional tool of Kalman Filters can be successfuly applied to do this task. We study two mean-reverting log-spot price models and the Pilipovic model using correspondingly Kalman Filter the extended Kalman Filter. The results of applying this method to market data from several power exchanges are discussed.

Keywords: Electricity markets; mean-reverting commodity prices; multifactor models; stochastic differential equations; Kalman Filters; calibration of market models; JEL classification code: C32; C52; Q40 (search for similar items in EconPapers)
Date: 2004
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Citations: View citations in EconPapers (10)

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DOI: 10.1142/S0219024904002396

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