IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i11p3345-d570264.html
   My bibliography  Save this article

Modeling Electricity Price and Quantity Uncertainty: An Application for Hedging with Forward Contracts

Author

Listed:
  • Alfredo Trespalacios

    (Department of Finance, Faculty of Economic and Administrative Sciences, Instituto Tecnológico Metropolitano, ITM, Medellin 050022, Colombia)

  • Lina M. Cortés

    (Department of Finance, School of Economics and Finance, Universidad EAFIT, Medellin 050022, Colombia)

  • Javier Perote

    (Department of Economics, Campus Miguel de Unamuno (Edif. FES), University of Salamanca and IME, 37007 Salamanca, Spain)

Abstract

Energy transactions in liberalized markets are subject to price and quantity uncertainty. This paper considers the spot price and energy generation to follow a bivariate semi-nonparametric distribution defined in terms of the Gram–Charlier expansion. This distribution allows us to jointly model not only mean, variance, and correlation but also skewness, kurtosis, and higher-order moments. Based on this model, we propose a static hedging strategy for electricity generators that participate in a competitive market where hedging is carried out through forward contracts that include a risk premium in their valuation. For this purpose, we use Monte Carlo simulation and consider information from the Colombian electricity market as the case study. The results show that the volume of energy to be sold under long-term contracts depends on each electricity generator and the risk assessment made by the market in the forward risk premium. The conditions of skewness, kurtosis, and correlation, as well as the type of the employed risk indicator, affect the hedging strategy that each electricity generator should implement. A positive correlation between the spot price and energy production tends to increase the hedge ratio; meanwhile, negative correlation tends to reduce it. The increase of forward risk premium, on the other hand, reduces the hedge ratio.

Suggested Citation

  • Alfredo Trespalacios & Lina M. Cortés & Javier Perote, 2021. "Modeling Electricity Price and Quantity Uncertainty: An Application for Hedging with Forward Contracts," Energies, MDPI, vol. 14(11), pages 1-26, June.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:11:p:3345-:d:570264
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/11/3345/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/11/3345/
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Jondeau, Eric & Rockinger, Michael, 2001. "Gram-Charlier densities," Journal of Economic Dynamics and Control, Elsevier, vol. 25(10), pages 1457-1483, October.
    2. Boroumand, Raphaël Homayoun & Goutte, Stéphane & Porcher, Simon & Porcher, Thomas, 2015. "Hedging strategies in energy markets: The case of electricity retailers," Energy Economics, Elsevier, vol. 51(C), pages 503-509.
    3. Botterud, Audun & Kristiansen, Tarjei & Ilic, Marija D., 2010. "The relationship between spot and futures prices in the Nord Pool electricity market," Energy Economics, Elsevier, vol. 32(5), pages 967-978, September.
    4. Lina M. Cortés & Andrés Mora-Valencia & Javier Perote, 2016. "The productivity of top researchers: a semi-nonparametric approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 891-915, November.
    5. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    6. Del Brio, Esther B. & Ñíguez, Trino-Manuel & Perote, Javier, 2011. "Multivariate semi-nonparametric distributions with dynamic conditional correlations," International Journal of Forecasting, Elsevier, vol. 27(2), pages 347-364.
    7. Cortés, Lina M. & Mora-Valencia, Andrés & Perote, Javier, 2017. "Measuring firm size distribution with semi-nonparametric densities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 485(C), pages 35-47.
    8. Christian Redl & Derek Bunn, 2013. "Determinants of the premium in forward contracts," Journal of Regulatory Economics, Springer, vol. 43(1), pages 90-111, January.
    9. Brunner, Allan D, 1992. "Conditional Asymmetries in Real GNP: A Seminonparametric Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(1), pages 65-72, January.
    10. Ñíguez, Trino-Manuel & Perote, Javier, 2016. "Multivariate moments expansion density: Application of the dynamic equicorrelation model," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 216-232.
    11. Esther B. Del Brio & Trino-Manuel Niguez & Javier Perote, 2009. "Gram-Charlier densities: a multivariate approach," Quantitative Finance, Taylor & Francis Journals, vol. 9(7), pages 855-868.
    12. Woo, Chi-Keung & Karimov, Rouslan I. & Horowitz, Ira, 2004. "Managing electricity procurement cost and risk by a local distribution company," Energy Policy, Elsevier, vol. 32(5), pages 635-645, March.
    13. Trino-Manuel Ñíguez & Javier Perote, 2012. "Forecasting Heavy-Tailed Densities with Positive Edgeworth and Gram-Charlier Expansions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(4), pages 600-627, August.
    14. Boroumand, Raphaël Homayoun & Goutte, Stéphane & Porcher, Simon & Porcher, Thomas, 2015. "Hedging strategies in energy markets: The case of electricity retailers," Energy Economics, Elsevier, vol. 51(C), pages 503-509.
    15. Trespalacios, Alfredo & Cortés, Lina M. & Perote, Javier, 2020. "Uncertainty in electricity markets from a semi-nonparametric approach," Energy Policy, Elsevier, vol. 137(C).
    16. Del Brio, Esther B. & Mora-Valencia, Andrés & Perote, Javier, 2017. "The kidnapping of Europe: High-order moments' transmission between developed and emerging markets," Emerging Markets Review, Elsevier, vol. 31(C), pages 96-115.
    17. Geman, Hélyette & Roncoroni, Andrea, 2003. "A Class of Marked Point Processes for Modelling Electricity Prices," ESSEC Working Papers DR 03004, ESSEC Research Center, ESSEC Business School.
    18. Javier Perote, 2004. "The multivariate Edgeworth-Sargan density," Spanish Economic Review, Springer;Spanish Economic Association, vol. 6(1), pages 77-96, April.
    19. Yumi Oum & Shmuel S. Oren, 2010. "Optimal Static Hedging of Volumetric Risk in a Competitive Wholesale Electricity Market," Decision Analysis, INFORMS, vol. 7(1), pages 107-122, March.
    20. Ruddell, Keith & Downward, Anthony & Philpott, Andy, 2018. "Market power and forward prices," Economics Letters, Elsevier, vol. 166(C), pages 6-9.
    21. Unknown, 2005. "Forward," 2005 Conference: Slovenia in the EU - Challenges for Agriculture, Food Science and Rural Affairs, November 10-11, 2005, Moravske Toplice, Slovenia 183804, Slovenian Association of Agricultural Economists (DAES).
    22. Bunn, Derek W. & Chen, Dipeng, 2013. "The forward premium in electricity futures," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 173-186.
    23. Mosquera-López, Stephanía & Uribe, Jorge M. & Manotas-Duque, Diego Fernando, 2017. "Nonlinear empirical pricing in electricity markets using fundamental weather factors," Energy, Elsevier, vol. 139(C), pages 594-605.
    24. Francis A. Longstaff & Ashley W. Wang, 2004. "Electricity Forward Prices: A High-Frequency Empirical Analysis," Journal of Finance, American Finance Association, vol. 59(4), pages 1877-1900, August.
    25. Ignacio Mauleon & Javier Perote, 2000. "Testing densities with financial data: an empirical comparison of the Edgeworth-Sargan density to the Student's t," The European Journal of Finance, Taylor & Francis Journals, vol. 6(2), pages 225-239.
    26. Javier Orlando Pantoja Robayo & Juan Fernando Rendón García & Alfredo Trespalacios Carrasquilla, 2012. "Estrategia de Cobertura a Través de Contratos Forward en Mercados Eléctricos," Documentos de Trabajo de Valor Público 10665, Universidad EAFIT.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Inés Jiménez & Andrés Mora-Valencia & Javier Perote, 2022. "Dynamic selection of Gram–Charlier expansions with risk targets: an application to cryptocurrencies," Risk Management, Palgrave Macmillan, vol. 24(1), pages 81-99, March.
    2. Jiménez, Inés & Mora-Valencia, Andrés & Perote, Javier, 2023. "Multivariate dynamics between emerging markets and digital asset markets: An application of the SNP-DCC model," Emerging Markets Review, Elsevier, vol. 56(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alfredo Trespalacios & Lina M. Cortés & Javier Perote, 2019. "Modeling the electricity spot price with switching regime semi-nonparametric distributions," Documentos de Trabajo de Valor Público 17618, Universidad EAFIT.
    2. Trespalacios, Alfredo & Cortés, Lina M. & Perote, Javier, 2020. "Uncertainty in electricity markets from a semi-nonparametric approach," Energy Policy, Elsevier, vol. 137(C).
    3. Jiménez, Inés & Mora-Valencia, Andrés & Perote, Javier, 2023. "Multivariate dynamics between emerging markets and digital asset markets: An application of the SNP-DCC model," Emerging Markets Review, Elsevier, vol. 56(C).
    4. Andrés Mora-Valencia & Trino-Manuel Ñíguez & Javier Perote, 2017. "Multivariate approximations to portfolio return distribution," Computational and Mathematical Organization Theory, Springer, vol. 23(3), pages 347-361, September.
    5. Ñíguez, Trino-Manuel & Perote, Javier, 2017. "Moments expansion densities for quantifying financial risk," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 53-69.
    6. Del Brio, Esther B. & Perote, Javier, 2012. "Gram–Charlier densities: Maximum likelihood versus the method of moments," Insurance: Mathematics and Economics, Elsevier, vol. 51(3), pages 531-537.
    7. Ñíguez, Trino-Manuel & Perote, Javier, 2016. "Multivariate moments expansion density: Application of the dynamic equicorrelation model," Journal of Banking & Finance, Elsevier, vol. 72(S), pages 216-232.
    8. van Koten, Silvester, 2021. "The forward premium in electricity markets: An experimental study," Energy Economics, Elsevier, vol. 94(C).
    9. Weron, Rafał & Zator, Michał, 2014. "Revisiting the relationship between spot and futures prices in the Nord Pool electricity market," Energy Economics, Elsevier, vol. 44(C), pages 178-190.
    10. Bevin-McCrimmon, Fergus & Diaz-Rainey, Ivan & McCarten, Matthew & Sise, Greg, 2018. "Liquidity and risk premia in electricity futures," Energy Economics, Elsevier, vol. 75(C), pages 503-517.
    11. Del Brio, Esther B. & Mora-Valencia, Andrés & Perote, Javier, 2017. "The kidnapping of Europe: High-order moments' transmission between developed and emerging markets," Emerging Markets Review, Elsevier, vol. 31(C), pages 96-115.
    12. Del Brio, Esther B. & Mora-Valencia, Andrés & Perote, Javier, 2014. "Semi-nonparametric VaR forecasts for hedge funds during the recent crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 330-343.
    13. Koten, Silvester Van, 2020. "Forward premia in electricity markets: A replication study," Energy Economics, Elsevier, vol. 89(C).
    14. Inés Jiménez & Andrés Mora-Valencia & Javier Perote, 2022. "Dynamic selection of Gram–Charlier expansions with risk targets: an application to cryptocurrencies," Risk Management, Palgrave Macmillan, vol. 24(1), pages 81-99, March.
    15. Inés Jiménez & Andrés Mora-Valencia & Trino-Manuel Ñíguez & Javier Perote, 2020. "Portfolio Risk Assessment under Dynamic (Equi)Correlation and Semi-Nonparametric Estimation: An Application to Cryptocurrencies," Mathematics, MDPI, vol. 8(12), pages 1-24, November.
    16. Del Brio, Esther B. & Mora-Valencia, Andrés & Perote, Javier, 2020. "Risk quantification for commodity ETFs: Backtesting value-at-risk and expected shortfall," International Review of Financial Analysis, Elsevier, vol. 70(C).
    17. Jiménez, Inés & Mora-Valencia, Andrés & Perote, Javier, 2022. "Semi-nonparametric risk assessment with cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 59(C).
    18. Russo, Marianna & Bertsch, Valentin, 2020. "A looming revolution: Implications of self-generation for the risk exposure of retailers," Energy Economics, Elsevier, vol. 92(C).
    19. Cortés, Lina M. & Mora-Valencia, Andrés & Perote, Javier, 2017. "Measuring firm size distribution with semi-nonparametric densities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 485(C), pages 35-47.
    20. Fleten, Stein-Erik & Hagen, Liv Aune & Nygård, Maria Tandberg & Smith-Sivertsen, Ragnhild & Sollie, Johan M., 2015. "The overnight risk premium in electricity forward contracts," Energy Economics, Elsevier, vol. 49(C), pages 293-300.

    More about this item

    Keywords

    semi-nonparametric approach; multivariate distribution; electricity markets; forward contracts;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • L98 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Government Policy
    • Q2 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2021:i:11:p:3345-:d:570264. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.