Vázquez, Miguel and SánchezÚbeda, Eugenio F. and Berzosa, Ana and Barquín, Julián (2008): Shortterm evolution of forward curves and volatility in illiquid power market.
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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 longterm/shortterm decomposition, where the price is thought of as made up of two factors: A longterm equilibrium level and shortterm movements around the equilibrium. We use a nonparametric approach to model the equilibrium level of power prices, and a meanreverting process with GARCH volatility to describe the dynamics of the shortterm component. Then, the model is used to derive the expression of the shortterm 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
Item Type:  MPRA Paper 

Original Title:  Shortterm evolution of forward curves and volatility in illiquid power market 
Language:  English 
Keywords:  Forward curves;Power Markets;GARCH volatility;nonparametric regression 
Subjects:  C  Mathematical and Quantitative Methods > C3  Multiple or Simultaneous Equation Models; Multiple Variables > C32  TimeSeries Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models D  Microeconomics > D8  Information, Knowledge, and Uncertainty > D81  Criteria for DecisionMaking under Risk and Uncertainty D  Microeconomics > D8  Information, Knowledge, and Uncertainty > D84  Expectations; Speculations C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C14  Semiparametric and Nonparametric Methods: General C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C15  Statistical Simulation Methods: General 
Item ID:  8932 
Depositing User:  Miguel Vázquez 
Date Deposited:  04. Jun 2008 04:33 
Last Modified:  11. Feb 2013 10:09 
References:  Black, F. (1976). The pricing of commodity contracts. Journal of Financial Economics, 3: pp. 16779. Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31: pp. 30727. Borovkova, S. (2006). Detecting market transitions and energy futures risk management using principal components. The European Journal of Finance, 12: pp. 495512. Clewlow, L. and Strickland, C. (1999). A multifactor model for energy derivatives. University of Technology, Sydney. QFRG Research Paper Series 28. Deng, S. (1999). Financial methods in deregulated electricity markets. Ph.D. Thesis, University of California at Berkeley. Duffie, D. (2001). Dynamic asset pricing theory (3rd edition). Princeton, Princeton University Press. Escribano, Á., Peña, J. I. and Villaplana, P. (2002). Modeling electricity prices: International evidence. Departamento de Economía, Universidad Carlos III, Madrid. Working Paper 0227, Economic Series 08. Eydeland, A. and Wolyniec, K. (2003). Energy and power risk management: New developments in modeling, pricing, and hedging. John Wiley & Sons. Garcia, R., Ghysels, E. and Renault, E. (2004). The econometrics of option pricing. CIRANO. Working Paper 2004s04. Geman, H. and Roncoroni, A. (2002). A class of marked pont processes for modelling electricity prices. ESSEC. Working Paper. Hastie, T., Tibshirani, R. and Friedman, J. (2001). The elements of statistical learning. SpringerVerlag. Heston, S. L. and Nandi, S. (1997). A closed form GARCH option pricing model. Federal Reserve Bank of Atlanta. Working Paper 979. Lucia, J. J. and Schwartz, E. S. (2002). Electricity prices and power derivatives: Evidence from the Nordic Power Exchange. Review of Derivatives Research, 5: pp. 550. Lutkepohl, H. (1993). Introduction to multiple time series analysis. SpringerVerlag. Pilipovic, D. (1997). Energy risk: Valuing and managing energy derivatives. McGrawHill. SánchezÚbeda, E. F. (1999). Models for data Analysis: Contributions to automatic learning. PhD. Thesis. Universidad Pontificia Comillas. SánchezÚbeda, E. F. and Wehenkel, L. (1998). The Hinges Model: A onedimensional countinuous piecewise polynomial model. Information Processing and Management of Uncertainty in Knowledgebased Systems, Paris. Schwartz, E. S. (1997). The stochastic behavior of commodity prices: Implications for valuation and hedging. Journal of finance, 52 (3): pp. 92373. Schwartz, E. S. and Smith, J. E. (2000). Shortterm variations and longterm dynamics in commodity prices. Management Science, 46 (7): pp. 893911. Vázquez, M. and Barquín, J. (2007). Price and volatility dynamics in electricity markets: A fundamental approach with strategic interaction representation. Instituto de Investigación Tecnológica, Universidad Pontificia Comillas. IIT Working Paper. Ventosa, M., Baíllo, Á., Rivier, M. and Ramos, A. (2005). Electricity market modelling trends. Energy Policy, 3 (7): pp. 897913. 
URI:  http://mpra.ub.unimuenchen.de/id/eprint/8932 
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