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This paper presents trend prediction results based on backtesting of the European UnionEmissions Trading Scheme futures market. This is based on the Intercontinental Exchange from 2005to 2019. An alternative trend prediction strategy is taken that is predicated on an application of theFractal Market Hypothesis (FMH) in order to develop an indicator that is predictive of short termfuture behaviour. To achieve this, we consider that a change in the polarity of the Lyapunov-to-Volatility Ratio precedes an associated change in the trend of the European Union Allowances (EUAs)price signal. The application of the FMH in this case is demonstrated to provide a useful tool in orderto assess the likelihood of the market becoming bear or bull dominant, thereby helping to informcarbon trading investment decisions. Under specific conditions, Evolutionary Computing methodsare utilised in order to optimise specific trading execution points within a trend and improve thepotential profitability of trading returns. Although the approach may well be of value for generalenergy commodity futures trading (and indeed the wider financial and commodity derivativemarkets), this paper presents the application of an investment indicator for EUA carbon futures riskmodelling and investment trend analysis only.
Lamphiere, M.; Blackledge,J. & Kearney, D. (2021) Carbon Futures Trading and Short-Term Price Prediction: An Analysis Using theFractal Market Hypothesis and Evolutionary Computing. Mathematics 2021,9, 1005. DOI: 10.3390/math9091005