Vazquez, Miguel and Barquín, Julián (2009): A fundamental power price model with oligopolistic competition representation.
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Abstract
Most popular approaches for modeling electricity prices rely at present on microeconomics rationale. They aim to study the interaction between decisions of agents in the market, and usually represent the impact of uncertainty in such decisions in a simplified way. The usual methodology of microeconomics models is the study of the interaction between the profitmaximization problems faced by each of the firms. On the other hand, there is a growing literature that describes the power price dynamics from the financial standpoint, through the statement of a more or less complex stochastic process. However, this theoretical framework is based on the assumption of perfect competition, and therefore the stochastic process may not capture important features of price dynamics. In this paper, we suggest a mixed approach, in the sense that the price is thought of as the composition of a longterm component, where the strategic behavior is represented, and a shortterm source of uncertainty that agents cannot take into account when deciding their strategies. The complex distributional implications of the oligopolistic behavior of market players are then given by the longtermcomponent dynamics, whereas the shortterm component captures the uncertainty related to the operation of power systems. In addition, this modeling approach allows for a direct description of the longterm volatility of power markets, which is usually hard to estimate through statistical models.
Item Type:  MPRA Paper 

Original Title:  A fundamental power price model with oligopolistic competition representation 
Language:  English 
Keywords:  power markets; pricing models; market power; longterm/shortterm decomposition 
Subjects:  C  Mathematical and Quantitative Methods > C3  Multiple or Simultaneous Equation Models; Multiple Variables > C32  TimeSeries Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models L  Industrial Organization > L1  Market Structure, Firm Strategy, and Market Performance > L13  Oligopoly and Other Imperfect Markets Q  Agricultural and Natural Resource Economics; Environmental and Ecological Economics > Q4  Energy > Q40  General C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C15  Statistical Simulation Methods: General G  Financial Economics > G1  General Financial Markets > G13  Contingent Pricing; Futures Pricing C  Mathematical and Quantitative Methods > C7  Game Theory and Bargaining Theory > C72  Noncooperative Games 
Item ID:  15629 
Depositing User:  Miguel Vázquez 
Date Deposited:  10. Jun 2009 06:12 
Last Modified:  12. Feb 2013 13:18 
References:  Barquín, J., Centeno, E. and Reneses, J. (2004). Medium term generation programming in competitive environments: a new optimization approach for market equilibrium computing. IEE Proceedings  Generation, Transmission and Distribution, 151 (1): pp. 11926. Bessembinder, H. and Lemon, M. L. (2002). Equilibrium pricing and optimal hedging in electricity forward markets. Journal of Finance, 57 (3): pp. 134782. Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31: pp. 30727. Clewlow, L. and Strickland, C. (1999). A multifactor model for energy derivatives. Lacima Articles. Day, C. J., Hobbs, B. F. and Pang, J.S. (2002). Oligopolistic competition in power networks: a conjectured supply function approach. IEEE Transactions on Power Systems, 17 (3): pp. 597607. 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. Eydeland, A. and Geman, H. (1998). Pricing power derivatives. Risk. Eydeland, A. and Wolyniec, K. (2003). Energy and power risk management: new developments in modeling, pricing, and hedging. John Wiley & Sons. Geman, H. and Roncoroni, A. (2002). A class of marked pont processes for modelling electricity prices. ESSEC. Working Paper. Hastie, T. J. and Tibshirani, R. J. (1990). Generalized additive models. London, Chapman and Hall. Klemperer, P. D. and Meyer, M. A. (1989). Supply function equilibria in oligopoly under uncertainty. Econometrica, 57 (6): pp. 124377. 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. Lütkepohl, H. (1993). Introduction to multiple time series analysis. SpringerVerlag. Metzler, C., Hobbs, B. F. and Pang, J. S. (2003). NashCournot equilibria in power markets on a linearized DC network with arbitrage: formulations and properties. Networks and Spatial Economics, 3 (2): pp. 12350. Neuhoff, K., Barquín, J., Boots, M. G., Ehrenmann, A., Hobbs, B. F., Rijkers, F. A. M. and Vázquez, M. (2005). Networkconstrained Cournot models of liberalized electricity markets: the devil is in te details. Energy Econoomics, 27: pp. 495525. Pilipovic, D. (1997). Energy risk: valuing and managing energy derivatives. McGrawHill. Pindyck, R. S. (1999). The longrun evolution of energy prices. The Energy Journal, 20 (2). Pirrong, C. and Jermakyan, M. (1999). Valuing power and weather derivatives on a mesh using finite difference methods. Risk Books. Scott, T. J. and Read, E. G. (1996). Modelling hydro reservoir operation in a deregulated electricity market. International Transactions in Operational Research, 3: pp. 24353. 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. Skantze, P. L. and Illic, M. D. (2001). Valuation, hedging and speculation in competitive electricity markets: A fundamental approach. Kluwer Academic Publishers Group. Weron, R. (2006). Modeling and forecasting electricity load and prices. Wiley. Yuan, W. J.. and Smeers, Y. (1999). Spatial oligopolistic electricity models with Cournot generators and regulated transmission prices. Operations Research, 47 (1): pp. 10212. 
URI:  http://mpra.ub.unimuenchen.de/id/eprint/15629 
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