IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i19p6930-d921619.html
   My bibliography  Save this article

The Impact of Coskewness and Cokurtosis as Augmentation Factors in Modeling Colombian Electricity Price Returns

Author

Listed:
  • Edgardo Cayon

    (Finance Department, CESA Business School, Bogotá 111311, Colombia)

  • Julio Sarmiento

    (Business Department, Pontificia Universidad Javeriana, Bogotá 110231, Colombia)

Abstract

This paper explores the empirical validity of an augmented volume model for Colombian electricity price returns (in the present study, the definition of returns is simply the “rate of change” of observed prices for different periods). Of particular interest is the impact of coskewness and cokurtosis when modeling Colombian electricity price returns. We found that coskewness as an augmentation factor is highly significant and should be considered when modeling Colombian electricity price returns. The results obtained for coskewness as an augmentation factor in a volume model are consistent when using either an Ordinary Least Square (OLS) and Generalized Method of Moments (GMM) specification for the data employed. On the other hand, the effect of cokurtosis is highly irrelevant and not significant in most cases under the proposed specification.

Suggested Citation

  • Edgardo Cayon & Julio Sarmiento, 2022. "The Impact of Coskewness and Cokurtosis as Augmentation Factors in Modeling Colombian Electricity Price Returns," Energies, MDPI, vol. 15(19), pages 1-8, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:19:p:6930-:d:921619
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/19/6930/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/19/6930/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jidong Wang & Jiahui Wu & Yingchen Shi, 2022. "A Novel Energy Management Optimization Method for Commercial Users Based on Hybrid Simulation of Electricity Market Bidding," Energies, MDPI, vol. 15(12), pages 1-24, June.
    2. Crespo Cuaresma, Jesús & Hlouskova, Jaroslava & Kossmeier, Stephan & Obersteiner, Michael, 2004. "Forecasting electricity spot-prices using linear univariate time-series models," Applied Energy, Elsevier, vol. 77(1), pages 87-106, January.
    3. Angelica Gianfreda, 2010. "Volatility and Volume Effects in European Electricity Spot Markets," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 39(1‐2), pages 47-63, February.
    4. Jagannathan, Ravi & Skoulakis, Georgios & Wang, Zhenyu, 2002. "Generalized Method of Moments: Applications in Finance," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 470-481, October.
    5. Knittel, Christopher R. & Roberts, Michael R., 2005. "An empirical examination of restructured electricity prices," Energy Economics, Elsevier, vol. 27(5), pages 791-817, September.
    6. Ioannidis, Filippos & Kosmidou, Kyriaki & Savva, Christos & Theodossiou, Panayiotis, 2021. "Electricity pricing using a periodic GARCH model with conditional skewness and kurtosis components," Energy Economics, Elsevier, vol. 95(C).
    7. Hendrik Bessembinder & Michael L. Lemmon, 2002. "Equilibrium Pricing and Optimal Hedging in Electricity Forward Markets," Journal of Finance, American Finance Association, vol. 57(3), pages 1347-1382, June.
    8. 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.
    9. Terry Robinson, 2000. "Electricity pool prices: a case study in nonlinear time-series modelling," Applied Economics, Taylor & Francis Journals, vol. 32(5), pages 527-532.
    10. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    11. Luiz Moreira Coelho Junior & Amadeu Junior da Silva Fonseca & Roberto Castro & João Carlos de Oliveira Mello & Victor Hugo Ribeiro dos Santos & Renato Barros Pinheiro & Wilton Lima Sousa & Edvaldo Per, 2022. "Empirical Evidence of the Cost of Capital under Risk Conditions for Thermoelectric Power Plants in Brazil," Energies, MDPI, vol. 15(12), pages 1-12, June.
    12. Fang, Hsing & Lai, Tsong-Yue, 1997. "Co-Kurtosis and Capital Asset Pricing," The Financial Review, Eastern Finance Association, vol. 32(2), pages 293-307, May.
    13. Tarun Chordia & Sahn-Wook Huh & Avanidhar Subrahmanyam, 2009. "Theory-Based Illiquidity and Asset Pricing," The Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3629-3668, September.
    14. Ramiz Qussous & Nick Harder & Anke Weidlich, 2022. "Understanding Power Market Dynamics by Reflecting Market Interrelations and Flexibility-Oriented Bidding Strategies," Energies, MDPI, vol. 15(2), pages 1-24, January.
    15. Vendrame, Vasco & Tucker, Jon & Guermat, Cherif, 2016. "Some extensions of the CAPM for individual assets," International Review of Financial Analysis, Elsevier, vol. 44(C), pages 78-85.
    16. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    17. Alvaro Escribano & J. Ignacio Peña & Pablo Villaplana, 2011. "Modelling Electricity Prices: International Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(5), pages 622-650, October.
    18. Kraus, Alan & Litzenberger, Robert H, 1976. "Skewness Preference and the Valuation of Risk Assets," Journal of Finance, American Finance Association, vol. 31(4), pages 1085-1100, September.
    19. Friend, Irwin & Westerfield, Randolph, 1980. "Co-Skewness and Capital Asset Pricing," Journal of Finance, American Finance Association, vol. 35(4), pages 897-913, September.
    20. Annika Gillich & Kai Hufendiek, 2022. "Asset Profitability in the Electricity Sector: An Iterative Approach in a Linear Optimization Model," Energies, MDPI, vol. 15(12), pages 1-31, June.
    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. Oscar G. Duarte & Javier A. Rosero & María del Carmen Pegalajar, 2022. "Data Preparation and Visualization of Electricity Consumption for Load Profiling," Energies, MDPI, vol. 15(20), pages 1-30, October.

    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. Ikeda, Shin S., 2019. "Illiquidity in the Japan electric power exchange," Journal of Commodity Markets, Elsevier, vol. 14(C), pages 16-39.
    2. Bowden, Nicholas & Payne, James E., 2008. "Short term forecasting of electricity prices for MISO hubs: Evidence from ARIMA-EGARCH models," Energy Economics, Elsevier, vol. 30(6), pages 3186-3197, November.
    3. Ketterer, Janina C., 2014. "The impact of wind power generation on the electricity price in Germany," Energy Economics, Elsevier, vol. 44(C), pages 270-280.
    4. Ayadi, Mohamed A. & Cao, Xu & Lazrak, Skander & Wang, Yan, 2019. "Do idiosyncratic skewness and kurtosis really matter?," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    5. Chabi-Yo, Fousseni & Ruenzi, Stefan & Weigert, Florian, 2018. "Crash Sensitivity and the Cross Section of Expected Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(3), pages 1059-1100, June.
    6. Racicot, François-Éric & Théoret, Raymond, 2018. "Multi-moment risk, hedging strategies, & the business cycle," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 637-675.
    7. Vendrame, Vasco & Guermat, Cherif & Tucker, Jon, 2023. "A conditional higher-moment CAPM," International Review of Financial Analysis, Elsevier, vol. 86(C).
    8. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601.
    9. Goto, Mika & Karolyi, G. Andrew, 2004. "Understanding Electricity Price Volatility within and across Markets," Working Paper Series 2004-12, Ohio State University, Charles A. Dice Center for Research in Financial Economics.
    10. 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.
    11. Rhee, S. Ghon & Wu, Feng (Harry), 2020. "Conditional extreme risk, black swan hedging, and asset prices," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 412-435.
    12. Ali, Heba, 2019. "Does downside risk matter more in asset pricing? Evidence from China," Emerging Markets Review, Elsevier, vol. 39(C), pages 154-174.
    13. Michel Culot & Valérie Goffin & Steve Lawford & Sébastien de Meten & Yves Smeers, 2013. "Practical stochastic modelling of electricity prices," Post-Print hal-01021603, HAL.
    14. Jiang, Lei, 2014. "Stock liquidity and the Taylor rule," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 202-214.
    15. 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.
    16. Scott Condie & Lars Stentoft & Marie-Louise Vierø, 2023. "Unawareness Premia," Economics Working Papers 2023-09, Department of Economics and Business Economics, Aarhus University.
    17. Lu, Ye & Suthaharan, Neyavan, 2023. "Electricity price spike clustering: A zero-inflated GARX approach," Energy Economics, Elsevier, vol. 124(C).
    18. Kosater, Peter & Mosler, Karl, 2006. "Can Markov regime-switching models improve power-price forecasts? Evidence from German daily power prices," Applied Energy, Elsevier, vol. 83(9), pages 943-958, September.
    19. Guthrie, Graeme & Videbeck, Steen, 2007. "Electricity spot price dynamics: Beyond financial models," Energy Policy, Elsevier, vol. 35(11), pages 5614-5621, November.
    20. Timothy Christensen & Stan Hurn & Kenneth Lindsay, 2009. "It Never Rains but it Pours: Modeling the Persistence of Spikes in Electricity Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 25-48.

    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:15:y:2022:i:19:p:6930-:d:921619. 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.