IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-10-00104.html
   My bibliography  Save this article

Volatility forecasting of carbon prices using factor models

Author

Listed:
  • Julien Chevallier

    (Université Paris Dauphine)

Abstract

This article develops a forecasting exercise of the volatility of EUA spot, EUA futures, and CER futures carbon prices (modeled after an AR(1)-GARCH(1,1)) using two dynamic factors as exogenous regressors that were extracted from a Factor Augmented VAR model (Bernanke et al. (2005)). The dataset includes 115 macroeconomic, financial and commodities indicators with daily frequency from April 4, 2008 through January 25, 2010 totalling 463 observations that capture the strong uncertainties emerging on the carbon market. The main result shows that the best forecasting performance for the volatility of carbon prices is achieved for the model including the dynamic factors as exogenous regressors, which can be useful to inform hedging or speculative trading strategies by energy utilities, financial market players and risk managers.

Suggested Citation

  • Julien Chevallier, 2010. "Volatility forecasting of carbon prices using factor models," Economics Bulletin, AccessEcon, vol. 30(2), pages 1642-1660.
    • Handle: RePEc:ebl:ecbull:eb-10-00104
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/Pubs/EB/2010/Volume30/EB-10-V30-I2-P151.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chevallier, Julien, 2009. "Carbon futures and macroeconomic risk factors: A view from the EU ETS," Energy Economics, Elsevier, vol. 31(4), pages 614-625, July.
    2. Chevallier, Julien, 2010. "Modelling risk premia in CO2 allowances spot and futures prices," Economic Modelling, Elsevier, vol. 27(3), pages 717-729, May.
    3. repec:dau:papers:123456789/4210 is not listed on IDEAS
    4. Daskalakis, George & Psychoyios, Dimitris & Markellos, Raphael N., 2009. "Modeling CO2 emission allowance prices and derivatives: Evidence from the European trading scheme," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1230-1241, July.
    5. Stock J.H. & Watson M.W., 2002. "Forecasting Using Principal Components From a Large Number of Predictors," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1167-1179, December.
    6. repec:dau:papers:123456789/4227 is not listed on IDEAS
    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. Zhu, Bangzhu & Ma, Shujiao & Chevallier, Julien & Wei, Yiming, 2014. "Modelling the dynamics of European carbon futures price: A Zipf analysis," Economic Modelling, Elsevier, vol. 38(C), pages 372-380.
    2. Byun, Suk Joon & Cho, Hangjun, 2013. "Forecasting carbon futures volatility using GARCH models with energy volatilities," Energy Economics, Elsevier, vol. 40(C), pages 207-221.
    3. Quande Qin & Huangda He & Li Li & Ling-Yun He, 2020. "A Novel Decomposition-Ensemble Based Carbon Price Forecasting Model Integrated with Local Polynomial Prediction," Computational Economics, Springer;Society for Computational Economics, vol. 55(4), pages 1249-1273, April.
    4. Wang, Jiqian & Guo, Xiaozhu & Tan, Xueping & Chevallier, Julien & Ma, Feng, 2023. "Which exogenous driver is informative in forecasting European carbon volatility: Bond, commodity, stock or uncertainty?," Energy Economics, Elsevier, vol. 117(C).
    5. Yumin Li & Ruiqi Yang & Xiaoman Wang & Jiaming Zhu & Nan Song, 2023. "Carbon Price Combination Forecasting Model Based on Lasso Regression and Optimal Integration," Sustainability, MDPI, vol. 15(12), pages 1-26, June.
    6. Jianguo Zhou & Xuejing Huo & Xiaolei Xu & Yushuo Li, 2019. "Forecasting the Carbon Price Using Extreme-Point Symmetric Mode Decomposition and Extreme Learning Machine Optimized by the Grey Wolf Optimizer Algorithm," Energies, MDPI, vol. 12(5), pages 1-22, March.
    7. Zhao, Xin & Han, Meng & Ding, Lili & Kang, Wanglin, 2018. "Usefulness of economic and energy data at different frequencies for carbon price forecasting in the EU ETS," Applied Energy, Elsevier, vol. 216(C), pages 132-141.
    8. Huang, Yumeng & Dai, Xingyu & Wang, Qunwei & Zhou, Dequn, 2021. "A hybrid model for carbon price forecastingusing GARCH and long short-term memory network," Applied Energy, Elsevier, vol. 285(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. Gil-Alana, Luis A. & Gupta, Rangan & de Gracia, Fernando Perez, 2016. "Modeling persistence of carbon emission allowance prices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 221-226.
    2. Reboredo, Juan C. & Ugando, Mikel, 2015. "Downside risks in EU carbon and fossil fuel markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 111(C), pages 17-35.
    3. Fang, Sheng & Lu, Xinsheng & Li, Jianfeng & Qu, Ling, 2018. "Multifractal detrended cross-correlation analysis of carbon emission allowance and stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 551-566.
    4. Marc Gronwald & Janina Ketterer & Stefan Trück, 2011. "The Dependence Structure between Carbon Emission Allowances and Financial Markets - A Copula Analysis," CESifo Working Paper Series 3418, CESifo.
    5. Xiaojian Su & Chao Deng, 2019. "The heterogeneous effects of exchange rate and stock market on CO2 emission allowance price in China: A panel quantile regression approach," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-11, August.
    6. repec:ipg:wpaper:2014-082 is not listed on IDEAS
    7. Julien Chevallier & Stéphane Goutte, 2014. "The goodness-of-fit of the fuel-switching price using the mean-reverting Lévy jump process," Working Papers 2014-285, Department of Research, Ipag Business School.
    8. Wen, Xiaoqian & Bouri, Elie & Roubaud, David, 2017. "Can energy commodity futures add to the value of carbon assets?," Economic Modelling, Elsevier, vol. 62(C), pages 194-206.
    9. Alexander Zeitlberger & Alexander Brauneis, 2016. "Modeling carbon spot and futures price returns with GARCH and Markov switching GARCH models," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 24(1), pages 149-176, March.
    10. Po Yun & Chen Zhang & Yaqi Wu & Yu Yang, 2022. "Forecasting Carbon Dioxide Price Using a Time-Varying High-Order Moment Hybrid Model of NAGARCHSK and Gated Recurrent Unit Network," IJERPH, MDPI, vol. 19(2), pages 1-19, January.
    11. Cong, Ren & Lo, Alex Y., 2017. "Emission trading and carbon market performance in Shenzhen, China," Applied Energy, Elsevier, vol. 193(C), pages 414-425.
    12. Thijs Benschopa & Brenda López Cabrera, 2014. "Volatility Modelling of CO2 Emission Allowance Spot Prices with Regime-Switching GARCH Models," SFB 649 Discussion Papers SFB649DP2014-050, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    13. Charles, Amélie & Darné, Olivier & Fouilloux, Jessica, 2011. "Testing the martingale difference hypothesis in CO2 emission allowances," Economic Modelling, Elsevier, vol. 28(1), pages 27-35.
    14. John Hua Fan & Eduardo Roca & Alexandr Akimov, 2014. "Estimation and performance evaluation of optimal hedge ratios in the carbon market of the European Union Emissions Trading Scheme," Australian Journal of Management, Australian School of Business, vol. 39(1), pages 73-91, February.
    15. Hammoudeh, Shawkat & Nguyen, Duc Khuong & Sousa, Ricardo M., 2014. "Energy prices and CO2 emission allowance prices: A quantile regression approach," Energy Policy, Elsevier, vol. 70(C), pages 201-206.
    16. Chevallier, Julien, 2011. "Detecting instability in the volatility of carbon prices," Energy Economics, Elsevier, vol. 33(1), pages 99-110, January.
    17. Nicolas Koch, 2014. "Dynamic linkages among carbon, energy and financial markets: a smooth transition approach," Applied Economics, Taylor & Francis Journals, vol. 46(7), pages 715-729, March.
    18. Chevallier, Julien, 2011. "Macroeconomics, finance, commodities: Interactions with carbon markets in a data-rich model," Economic Modelling, Elsevier, vol. 28(1), pages 557-567.
    19. Conrad, Christian & Rittler, Daniel & Rotfuß, Waldemar, 2012. "Modeling and explaining the dynamics of European Union Allowance prices at high-frequency," Energy Economics, Elsevier, vol. 34(1), pages 316-326.
    20. Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2020. "How connected is the carbon market to energy and financial markets? A systematic analysis of spillovers and dynamics," Energy Economics, Elsevier, vol. 90(C).
    21. Gavard, Claire & Kirat, Djamel, 2018. "Flexibility in the market for international carbon credits and price dynamics difference with European allowances," Energy Economics, Elsevier, vol. 76(C), pages 504-518.

    More about this item

    Keywords

    Volatility Forecasting; Carbon price; Factor models;
    All these keywords.

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

    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:ebl:ecbull:eb-10-00104. 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: John P. Conley (email available below). General contact details of provider: .

    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.