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Why do carbon prices and price volatility change?

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  • Ibrahim, Boulis Maher
  • Kalaitzoglou, Iordanis Angelos

Abstract

An asymmetric information microstructural pricing model is proposed in which price responses to information and liquidity vary with every transaction. bid-ask quotes and price components account for learning by incorporating changing expectations of the rate of transacted volume (trading intensity) and the risk level of incoming trades. Analysis of European carbon futures transactions finds expected trading intensity to simultaneously increase the information component and decrease the liquidity component of price changes, but at different rates. This explains some conflicting results in prior literature. Further, the expected persistence in trading intensity explains the majority of the autocorrelations in the level and the conditional variance of price change; helps predict hourly patterns in returns, variance and the bid-ask spread; and differentiates the price impact of buy versus sell and continuing versus reversing trades.

Suggested Citation

  • Ibrahim, Boulis Maher & Kalaitzoglou, Iordanis Angelos, 2016. "Why do carbon prices and price volatility change?," Journal of Banking & Finance, Elsevier, vol. 63(C), pages 76-94.
  • Handle: RePEc:eee:jbfina:v:63:y:2016:i:c:p:76-94
    DOI: 10.1016/j.jbankfin.2015.11.004
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    2. Federico Galán-Valdivieso & Elena Villar-Rubio & María-Dolores Huete-Morales, 2018. "The erratic behaviour of the EU ETS on the path towards consolidation and price stability," International Environmental Agreements: Politics, Law and Economics, Springer, vol. 18(5), pages 689-706, October.
    3. Wenjun Chu & Shanglei Chai & Xi Chen & Mo Du, 2020. "Does the Impact of Carbon Price Determinants Change with the Different Quantiles of Carbon Prices? Evidence from China ETS Pilots," Sustainability, MDPI, Open Access Journal, vol. 12(14), pages 1-19, July.
    4. Rannou, Yves, 2019. "Limit order books, uninformed traders and commodity derivatives: Insights from the European carbon futures," Economic Modelling, Elsevier, vol. 81(C), pages 387-410.
    5. Duan, Kun & Ren, Xiaohang & Shi, Yukun & Mishra, Tapas & Yan, Cheng, 2021. "The marginal impacts of energy prices on carbon price variations: Evidence from a quantile-on-quantile approach," Energy Economics, Elsevier, vol. 95(C).
    6. Diogo José Horst, 2020. "A Short Review on Carbon Footprint," Open Access Journal Of Environmental & Soil Science, Lupine Publishers, LLC, vol. 5(3), pages 642-651, July.
    7. Friedrich, Marina & Mauer, Eva-Maria & Pahle, Michael & Tietjen, Oliver, 2020. "From fundamentals to financial assets: the evolution of understanding price formation in the EU ETS," EconStor Preprints 196150, ZBW - Leibniz Information Centre for Economics.
    8. Tan, Xue-Ping & Wang, Xin-Yu, 2017. "Dependence changes between the carbon price and its fundamentals: A quantile regression approach," Applied Energy, Elsevier, vol. 190(C), pages 306-325.
    9. Chai, Shanglei & Zhou, P., 2018. "The Minimum-CVaR strategy with semi-parametric estimation in carbon market hedging problems," Energy Economics, Elsevier, vol. 76(C), pages 64-75.

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    More about this item

    Keywords

    CO2 emission allowances; Market microstructure; Duration; Liquidity; Price discovery;
    All these keywords.

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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