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Modelling Correlation in Carbon and Energy Markets

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  • Koenig, P.

Abstract

The paper examines correlations between daily returns of month-ahead baseload electricity, fuel input and carbon emission allowance (EU-ETS) prices for Great Britain. The perspective of a CCGT plant operator is assumed, producing baseload electricity with natural gas and emission allowances and selling output forward in the month-ahead market. Price correlation between power, natural gas and emission allowances as well as their dynamic behaviour is essential for the extent to which cashflows from CCGT plants are self-hedged. Switching between input fuels with different carbon intensities is taken as the fundamental driver of this correlation. Relative marginal power generation costs are used to construct carbon price regimes during which no switching takes place. The regimes are then used as explanatory variables in a dynamic conditional correlation model. Using daily observations of month-ahead prices from April 2005 to August 2010, the results suggest that extreme weather, high commodity market volatility and seasons have no effect on correlation. However, there is evidence of significant price decoupling during periods of extreme relative carbon, coal and natural gas prices.

Suggested Citation

  • Koenig, P., 2011. "Modelling Correlation in Carbon and Energy Markets," Cambridge Working Papers in Economics 1123, Faculty of Economics, University of Cambridge.
    • Handle: RePEc:cam:camdae:1123
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    File URL: http://www.econ.cam.ac.uk/research-files/repec/cam/pdf/cwpe1123.pdf
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    Citations

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    Cited by:

    1. Michael G. Pollitt, 2019. "The European Single Market in Electricity: An Economic Assessment," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 55(1), pages 63-87, August.
    2. repec:eco:journ1:2014-03-21 is not listed on IDEAS
    3. Ren� Carmona & Michael Coulon & Daniel Schwarz, 2012. "The valuation of clean spread options: linking electricity, emissions and fuels," Quantitative Finance, Taylor & Francis Journals, vol. 12(12), pages 1951-1965, December.
    4. Adams, R. & Jamasb, J., 2016. "Optimal Power Generation Portfolios with Renewables: An Application to the UK," Cambridge Working Papers in Economics 1646, Faculty of Economics, University of Cambridge.
    5. Oscar Carchano & Vicente Medina Martínez & Ángel Pardo Tornero, 2012. "Rolling over EUAs and CERs," Working Papers. Serie AD 2012-15, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    6. Green, Rikard & Larsson, Karl & Lunina, Veronika & Nilsson, Birger, 2018. "Cross-commodity news transmission and volatility spillovers in the German energy markets," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 231-243.
    7. Yu, Jongmin & Mallory, Mindy L., 2014. "Exchange rate effect on carbon credit price via energy markets," Journal of International Money and Finance, Elsevier, vol. 47(C), pages 145-161.
    8. Galinato, Suzette P. & Yoder, Jonathan K. & Granatstein, David, 2011. "The economic value of biochar in crop production and carbon sequestration," Energy Policy, Elsevier, vol. 39(10), pages 6344-6350, October.
    9. Themistoclis Pantos & Stathis Polyzos & Aggelos Armenatzoglou & Ilias Kampouris, 2019. "Volatility Spillovers in Electricity Markets: Evidence from the United States," International Journal of Energy Economics and Policy, Econjournals, vol. 9(4), pages 131-143.
    10. 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.

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    More about this item

    Keywords

    EU-ETS; Natural Gas; Fuel-Switching; Dynamic Conditional Correlation;
    All these keywords.

    JEL classification:

    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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