Carbon Futures Trading and Short-Term Price Prediction: An Analysis Using the Fractal Market Hypothesis and Evolutionary Computing

This paper presents trend prediction results based on backtesting of the European Union Emissions Trading Scheme futures market. is Intercontinental Exchange from 2005 to 2019. An alternative strategy taken that predicated an application Fractal Market Hypothesis (FMH) in order develop indicator predictive short term future behaviour. To achieve this, we consider a change polarity Lyapunov-to-Volatility Ratio precedes associated Allowances (EUAs) price signal. The FMH this case demonstrated provide useful tool assess likelihood market becoming bear or bull dominant, thereby helping inform carbon trading investment decisions. Under specific conditions, Evolutionary Computing methods are utilised optimise execution points within and improve potential profitability returns. Although approach may well be value for general energy commodity (and indeed wider financial derivative markets), EUA risk modelling analysis only.