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Testing the martingale difference hypothesis in CO2 emission allowances

Author

Listed:
  • Amélie Charles

    (Audencia Recherche - Audencia Business School)

  • Olivier Darné

    (LEMNA - Laboratoire d'économie et de management de Nantes Atlantique - IEMN-IAE Nantes - Institut d'Économie et de Management de Nantes - Institut d'Administration des Entreprises - Nantes - UN - Université de Nantes)

  • Jessica Fouilloux

    (CREM - Centre de recherche en économie et management - UNICAEN - Université de Caen Normandie - NU - Normandie Université - UR - Université de Rennes - CNRS - Centre National de la Recherche Scientifique)

Abstract

This study examines the martingale difference hypothesis (MDH) for the carbon emission allowance market within the European Union Emission Trading Scheme (EU ETS) during the Phase I and the Phase II, using both daily and weekly data over the 2005-2009 period. We analyze the MDH for spot prices negotiated on BlueNext, European Energy Exchange and Nord Pool along with futures prices negotiated on BlueNext and European Climate Exchange, using the new variance ratio tests developed by Kim (2009) and the generalized spectral test proposed by Escanciano and Velasco (2006). For the Phase I, the results show that the spot price changes of these three markets are predictable, suggesting the possibility of abnormal returns through speculation, except during the period April 2006 to October 2006, namely after the compliance break and before the ECs of stricter NAP II. Finally, we find that the CO2 spot and futures price changes are unpredictable during the Phase II because we failed to reject the MDH based on both daily and weekly data. Thus, these markets are found to be weak-form efficient.

Suggested Citation

  • Amélie Charles & Olivier Darné & Jessica Fouilloux, 2011. "Testing the martingale difference hypothesis in CO2 emission allowances," Post-Print halshs-00600724, HAL.
    • Handle: RePEc:hal:journl:halshs-00600724
    DOI: 10.1016/j.econmod.2010.10.003
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    3. Yun-Jung Lee & Neung-Woo Kim & Ki-Hong Choi & Seong-Min Yoon, 2020. "Analysis of the Informational Efficiency of the EU Carbon Emission Trading Market: Asymmetric MF-DFA Approach," Energies, MDPI, vol. 13(9), pages 1-14, May.
    4. Carmen López-Martín & Sonia Benito Muela & Raquel Arguedas, 2021. "Efficiency in cryptocurrency markets: new evidence," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 403-431, September.
    5. Zdeněk Hlávka & Marie Hušková & Claudia Kirch & Simos G. Meintanis, 2017. "Fourier--type tests involving martingale difference processes," Econometric Reviews, Taylor & Francis Journals, vol. 36(4), pages 468-492, April.
    6. Chu, Baoju & Dong, Yizhe & Liu, Yaorong & Ma, Diandian & Wang, Tianju, 2024. "Does China's emission trading scheme affect corporate financial performance: Evidence from a quasi-natural experiment," Economic Modelling, Elsevier, vol. 132(C).
    7. Cristina Sattarhoff & Marc Gronwald, 2018. "How to Measure Financial Market Efficiency? A Multifractality-Based Quantitative Approach with an Application to the European Carbon Market," CESifo Working Paper Series 7102, CESifo.
    8. Eunyoung Kim & Youngcheul Ahn & Doojin Ryu, 2014. "Application of the Carbon Emission Pricing Model in the Korean Market," Energy & Environment, , vol. 25(1), pages 63-78, February.
    9. Zhang, Wei & Li, Jing & Li, Guoxiang & Guo, Shucen, 2020. "Emission reduction effect and carbon market efficiency of carbon emissions trading policy in China," Energy, Elsevier, vol. 196(C).
    10. Todea, Alexandru & Pleşoianu, Anita, 2013. "The influence of foreign portfolio investment on informational efficiency: Empirical evidence from Central and Eastern European stock markets," Economic Modelling, Elsevier, vol. 33(C), pages 34-41.
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    More about this item

    Keywords

    Market efficiency; CO2 emission allowances; Martingale difference hypothesis;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • Q53 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Air Pollution; Water Pollution; Noise; Hazardous Waste; Solid Waste; Recycling
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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