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Measuring informational efficiency of the European carbon market — A quantitative evaluation of higher order dependence
Institution:1. Department of Economics and Finance, College of Business Administration, Gulf University for Science & Technology, Hawally, West Mishref, Kuwait;2. Department of Economics, Faculty of Social Sciences, University of Ottawa, Ottawa, Canada;3. Center of Research for Energy and Climate Change (CRECC) - Paris School of Business, France;1. College of Business and Public Management, Wenzhou-Kean University, Wenzhou, China;2. Department of Economics and Finance, University of Castilla-La Mancha, Albacete, Spain
Abstract:This paper introduces a new method for measuring nonlinear predictability in financial price changes: the so-called intermittency coefficient, a parameter of the multifractal random walk model by Bacry et al. (2001). As the intermittency coefficient can quantify the degree of nonlinear deviation from a random walk, we employ its estimates from financial data as a proxy for the loss of financial market efficiency. In addition, we propose a new statistical test of the random walk hypothesis. In an empirical application using data from the largest currently existing market for tradable pollution permits, the European Union Emissions Trading Scheme (EU ETS), we show that the degree of efficiency of this market remains largely unchanged over the period of observation 2008–2019. This suggests that the market has reached a mature state: informational efficiency in Phase III remains at a level comparable to Phase II. What is more, the EU ETS is found to be more efficient than the US stock market. This result, surprising as such, is largely attributable to the lower exposure to global economic shocks of the EU ETS.
Keywords:Weak-form market efficiency  Degree of market efficiency  Multifractality  Multifractal random walk  European union emissions trading scheme
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