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ELECTRICITY FORWARD PRICES: A High-Frequency Empirical Analysis

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  • Longstaff, Francis A
  • Wang, Ashley

Abstract

We conduct an empirical analysis of electricity forward prices using a high-frequency data set of hourly spot and day-ahead forward prices. We find that there are significant risk premia in electricity forward prices. These premia vary systematically throughout the day and are directly related to economic risk factors such as the volatility of unexpected changes in prices and demand as well as the risk of price spikes. In contrast to the popular post-Enron view that electricity markets are easily manipulated, these results support the hypothesis that electricity forward prices are determined rationally by risk-averse economic agents.

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  • Longstaff, Francis A & Wang, Ashley, 2002. "ELECTRICITY FORWARD PRICES: A High-Frequency Empirical Analysis," University of California at Los Angeles, Anderson Graduate School of Management qt3mw4q41x, Anderson Graduate School of Management, UCLA.
  • Handle: RePEc:cdl:anderf:qt3mw4q41x
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    Cited by:

    1. Nomikos, Nikos K. & Soldatos, Orestes A., 2010. "Analysis of model implied volatility for jump diffusion models: Empirical evidence from the Nordpool market," Energy Economics, Elsevier, vol. 32(2), pages 302-312, March.
    2. Arciniegas, Ismael & Barrett, Chris & Marathe, Achla, 2003. "Assessing the efficiency of US electricity markets," Utilities Policy, Elsevier, vol. 11(2), pages 75-86, June.
    3. Martínez, Beatriz & Torró, Hipòlit, 2018. "Analysis of risk premium in UK natural gas futures," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 621-636.
    4. Villaplana Conde, Pablo, 2003. "Pricing power derivatives: a two-factor jump-diffusion approach," DEE - Working Papers. Business Economics. WB wb031805, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    5. Nomikos, Nikos K. & Soldatos, Orestes A., 2010. "Modelling short and long-term risks in power markets: Empirical evidence from Nord Pool," Energy Policy, Elsevier, vol. 38(10), pages 5671-5683, October.
    6. Modjtahedi, Bagher & Movassagh, Nahid, 2005. "Natural-gas futures: Bias, predictive performance, and the theory of storage," Energy Economics, Elsevier, vol. 27(4), pages 617-637, July.
    7. Baskette, C. & Horii, B. & Kollman, E. & Price, S., 2006. "Avoided cost estimation and post-reform funding allocation for California's energy efficiency programs," Energy, Elsevier, vol. 31(6), pages 1084-1099.
    8. Sandro Sapio, 2006. "An Empirically Based Model of the Supply Schedule in Day-Ahead Electricity Markets," LEM Papers Series 2006/12, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    9. Redl, Christian & Haas, Reinhard & Huber, Claus & Böhm, Bernhard, 2009. "Price formation in electricity forward markets and the relevance of systematic forecast errors," Energy Economics, Elsevier, vol. 31(3), pages 356-364, May.

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