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Short-term evolution of forward curves and volatility in illiquid power markets

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Author Info
Vázquez, Miguel
Sánchez-Úbeda, Eugenio F.
Berzosa, Ana
Barquín, Julián

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Abstract

We propose in this paper a model for the description of electricity spot prices, which we use to describe the dynamics of forward curves. The spot price model is based on a long-term/short-term decomposition, where the price is thought of as made up of two factors: A long-term equilibrium level and short-term movements around the equilibrium. We use a non-parametric approach to model the equilibrium level of power prices, and a mean-reverting process with GARCH volatility to describe the dynamics of the short-term component. Then, the model is used to derive the expression of the short-term dynamics of the forward curve implicit in spot prices. The rationale for the approach is that information concerning forward prices is not available in most of power markets, and the direct modeling of the forward curve is a difficult task. Moreover, power derivatives are typically written on forward contracts, and usually based on average prices of forward contracts. Then, it is difficult to obtain analytical expressions for the forward curves. The model of forward prices allows for the valuation of power derivatives, as well as the calculation of the volatilities and correlations required in risk management activities. Finally, the methodology is proven in the context of the Spanish wholesale market

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Publisher Info
Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 8932.

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Date of creation: Feb 2008
Date of revision: May 2008
Handle: RePEc:pra:mprapa:8932

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Related research
Keywords: Forward curves Power Markets GARCH volatility nonparametric regression

Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models
D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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References listed on IDEAS
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  1. Black, Fischer, 1976. "The pricing of commodity contracts," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 167-179. [Downloadable!] (restricted)
  2. Les Clewlow & Chris Strickland, 1999. "A Multi-Factor Model for Energy Derivatives," Research Paper Series 28, Quantitative Finance Research Centre, University of Technology, Sydney.
  3. René Garcia & Eric Ghysels & Éric Renault, 2004. "The Econometrics of Option Pricing," CIRANO Working Papers 2004s-04, CIRANO. [Downloadable!]
  4. Svetlana Borovkova, 2006. "Detecting market transitions and energy futures risk management using principal components," European Journal of Finance, Taylor and Francis Journals, vol. 12(6-7), pages 495-512, October. [Downloadable!] (restricted)
  5. Steven L. Heston & Saikat Nandi, 1997. "A closed-form GARCH option pricing model," Working Paper 97-9, Federal Reserve Bank of Atlanta. [Downloadable!]
  6. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April. [Downloadable!] (restricted)
  7. Álvaro Escribano & Juan Ignacio Peña & Pablo Villaplana, 2002. "Modeling Electricity Prices: International Evidence," Economics Working Papers we022708, Universidad Carlos III, Departamento de Economía. [Downloadable!]
  8. Schwartz, Eduardo S, 1997. " The Stochastic Behavior of Commodity Prices: Implications for Valuation and Hedging," Journal of Finance, American Finance Association, vol. 52(3), pages 923-73, July. [Downloadable!] (restricted)
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