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Is the Global Carbon Market Integrated? Return and Volatility Connectedness in ETS Systems

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Abstract

Emission trading is gaining momentum with its increasing market size and constantly improving information transmission mechanisms. With carbon assets becoming prominent as an alternative asset in investment portfolios, the ETS model has engaged a broad range of market participants, including not only emissions-intensive energy corporations but also individual and institutional investors. As arbitrage opportunities arise, price fluctuations are likely to occur, which typically have a mutual spillover effect. This paper examines how market fluctuations (e.g., volatilities) in these markets interact with each other, among carbon prices across four jurisdictions – European Union, New Zealand, California, and Hubei (China) ETS. The data used in this paper consists of weekly return and volatility, constructed by the daily prices from four markets, covering the period 30th April 2014, through 1st December 2021. We focus theoretically on the time-varying parameter (TVP)-VAR methodology, and empirically the connectedness approach. Our empirical results show average return (volatility) spillover is 6.03% (8.25%), which means that the dynamics of each of the carbon market are mainly explained by themselves and not due to spillovers from other markets, indicating that the global carbon prices are largely (albeit not completely) dependent.

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  • Lyu, Chenyan & Scholtens, Bert, 2022. "Is the Global Carbon Market Integrated? Return and Volatility Connectedness in ETS Systems," Working Papers 7-2022, Copenhagen Business School, Department of Economics, revised 08 Jun 2022.
    • Handle: RePEc:hhs:cbsnow:2022_007
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    Cited by:

    1. Philips, Abiodun S., 2023. "Institutional enforcement of environmental fiscal stance and energy stock markets performance: Evaluating for returns and risk among connected markets," Energy, Elsevier, vol. 263(PE).

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    More about this item

    Keywords

    Carbon markets integration; Volatility connectedness; TVP-VAR; Market risk;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes

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