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Modelling the Volatility of the Spanish Wholesale Electricity Spot Market. Asymmetric GARCH Models vs. Threshold ARSV model/Modelización de la volatilidad en el mercado eléctrico español. Modelos GARCH frente al modelo T-ARSV

Author

Listed:
  • MONTERO, JOSÉ M.

    () (Departamento de Estadística, UNIVERSITY OF CASTLLA-LA MANCHA, SPAIN.)

  • GARCÍA-CENTENO, MARIA C.

    () (Departamento de Estadística, UNIVERSITY OF SAN PABLO-CEU, SPAIN.)

  • FERNÁNDEZ-AVILÉS, GEMA

    () (Departamento de Estadística, UNIVERSITY OF CASTLLA-LA MANCHA, SPAIN.)

Abstract

The liberalization and deregulation of the Spanish electricity market has provoked an increase in the complexity of pricing behaviour. In particular, the volatility of electricity spot prices is the feature that best characterises the current Spanish market. Since an understanding of the volatility process in the electricity market is critically important to distributors, generators and market regulators, this article focuses on the asymmetrical pattern of the volatility of Spanish electricity spot prices, paying special attention to the direct or inverse leverage effect. For this purpose, we use both a range of traditional GARCH models and a T-ARSV model. The results clearly favour the proposed T-ARSV specification, which suggests a positive leverage effect in the Spanish market. El proceso de liberalización y desregulación del mercado eléctrico español ha incrementado la complejidad del comportamiento de los precios. En particular, la volatilidad de los precios spot es la característica que mejor define el mercado español actual. Teniendo en cuenta que el conocimiento de este hecho estilizado es clave para distribuidores, generadores y reguladores, en este artículo nos centramos en el estudio de la respuesta asimétrica o no de los precios spot, así como en la existencia de efecto leverage directo o inverso. Para ello se utiliza una batería de modelos GARCH tradicionales en la literatura, a la que se enfrenta el modelo de volatilidad T-ARSV. Los resultados favorecen a la especificación T-ARSV y sugieren un efecto leverage positivo en el mercado eléctrico español.

Suggested Citation

  • Montero, José M. & García-Centeno, Maria C. & Fernández-Avilés, Gema, 2011. "Modelling the Volatility of the Spanish Wholesale Electricity Spot Market. Asymmetric GARCH Models vs. Threshold ARSV model/Modelización de la volatilidad en el mercado eléctrico español. Modelos GARC," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 29, pages 597-616, Agosto.
  • Handle: RePEc:lrk:eeaart:29_2_10
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    References listed on IDEAS

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    1. Weron, R & Bierbrauer, M & Trück, S, 2004. "Modeling electricity prices: jump diffusion and regime switching," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(1), pages 39-48.
    2. Manabu Asai & Michael McAleer, 2006. "Asymmetric Multivariate Stochastic Volatility," Econometric Reviews, Taylor & Francis Journals, vol. 25(2-3), pages 453-473.
    3. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    4. Knittel, Christopher R. & Roberts, Michael R., 2005. "An empirical examination of restructured electricity prices," Energy Economics, Elsevier, vol. 27(5), pages 791-817, September.
    5. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July.
    6. Fong Chan, Kam & Gray, Philip, 2006. "Using extreme value theory to measure value-at-risk for daily electricity spot prices," International Journal of Forecasting, Elsevier, vol. 22(2), pages 283-300.
    7. Rafal Weron & Adam Misiorek, 2005. "Modeling and forecasting electricity loads: A comparison," Econometrics 0502004, EconWPA.
    8. Harvey, Andrew C & Shephard, Neil, 1996. "Estimation of an Asymmetric Stochastic Volatility Model for Asset Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 429-434, October.
    9. Siem Jan Koopman & Eugenie Hol Uspensky, 2002. "The stochastic volatility in mean model: empirical evidence from international stock markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(6), pages 667-689.
    10. Yu, Jun, 2005. "On leverage in a stochastic volatility model," Journal of Econometrics, Elsevier, vol. 127(2), pages 165-178, August.
    11. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    12. Angelica Gianfreda, 2010. "Volatility and Volume Effects in European Electricity Spot Markets," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 39(s1), pages 47-63, February.
    13. Ruiz, Esther & Veiga, Helena, 2008. "Modelling long-memory volatilities with leverage effect: A-LMSV versus FIEGARCH," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2846-2862, February.
    14. Worthington, Andrew & Kay-Spratley, Adam & Higgs, Helen, 2005. "Transmission of prices and price volatility in Australian electricity spot markets: a multivariate GARCH analysis," Energy Economics, Elsevier, vol. 27(2), pages 337-350, March.
    15. Bystrom, Hans N. E., 2005. "Extreme value theory and extremely large electricity price changes," International Review of Economics & Finance, Elsevier, vol. 14(1), pages 41-55.
    16. Abdou Kâ Diongue & Dominique Guegan, 2008. "The k-factor Gegenbauer asymmetric Power GARCH approach for modelling electricity spot price dynamics," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00259225, HAL.
    17. Lester Hadsell, Achla Marathe and Hany A. Shawky, 2004. "Estimating the Volatility of Wholesale Electricity Spot Prices in the US," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 23-40.
    18. So, Mike K P & Li, W K & Lam, K, 2002. "A Threshold Stochastic Volatility Model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(7), pages 473-500, November.
    19. Helen Higgs & Andrew C. Worthington, 2005. "Systematic Features of High-Frequency Volatility in Australian Electricity Markets: Intraday Patterns, Information Arrival and Calendar Effects," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 23-42.
    20. Smith Daniel R, 2009. "Asymmetry in Stochastic Volatility Models: Threshold or Correlation?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(3), pages 1-36, May.
    21. Engle, Robert F, 1990. "Stock Volatility and the Crash of '87: Discussion," Review of Financial Studies, Society for Financial Studies, vol. 3(1), pages 103-106.
    22. Huisman, Ronald & Mahieu, Ronald, 2003. "Regime jumps in electricity prices," Energy Economics, Elsevier, vol. 25(5), pages 425-434, September.
    23. José‐María Montero & Gema Fernández‐Avilés & María‐Carmen García, 2010. "Estimation of Asymmetric Stochastic Volatility Models: Application to Daily Average Prices of Energy Products," International Statistical Review, International Statistical Institute, vol. 78(3), pages 330-347, December.
    24. Sandmann, Gleb & Koopman, Siem Jan, 1998. "Estimation of stochastic volatility models via Monte Carlo maximum likelihood," Journal of Econometrics, Elsevier, vol. 87(2), pages 271-301, September.
    25. Weron, R. & Kozłowska, B. & Nowicka-Zagrajek, J., 2001. "Modeling electricity loads in California: a continuous-time approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 344-350.
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    Keywords

    Precios de electricidad; Volatilidad; GARCH; T-ARSV ; Electricity prices; volatility; GARCH; T-ARSV.;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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