
doi: 10.3390/math9091005
handle: 10566/6926
This paper presents trend prediction results based on backtesting of the European Union Emissions Trading Scheme futures market. This is based on the Intercontinental Exchange from 2005 to 2019. An alternative trend prediction strategy is taken that is predicated on an application of the Fractal Market Hypothesis (FMH) in order to develop an indicator that is predictive of short term future 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 order to assess the likelihood of the market becoming bear or bull dominant, thereby helping to inform carbon trading investment decisions. Under specific conditions, Evolutionary Computing methods are utilised in order to optimise specific trading execution points within a trend and improve the potential profitability of trading returns. Although the approach may well be of value for general energy commodity futures trading (and indeed the wider financial and commodity derivative markets), this paper presents the application of an investment indicator for EUA carbon futures risk modelling and investment trend analysis only.
330, stochastic field theory, lyapunov exponent, European Union Emissions Trading Scheme, Evolutionary computing, 332, Physical Sciences and Mathematics, evolutionary computing, QA1-939, future price prediction, Fractal market hypothesis, carbon trading, Fractal Market Hypothesis, future price prediction;carbon price risk assessment modelling, Carbon trading, carbon trading; European Union Emissions Trading Scheme; stochastic field theory;Fractal Market Hypothesis; lyapunov exponent; evolutionary computing; future price prediction;carbon price risk assessment modelling, Future price prediction, stochastic field theory;Fractal Market Hypothesis, carbon price risk assessment modelling, Mathematics
330, stochastic field theory, lyapunov exponent, European Union Emissions Trading Scheme, Evolutionary computing, 332, Physical Sciences and Mathematics, evolutionary computing, QA1-939, future price prediction, Fractal market hypothesis, carbon trading, Fractal Market Hypothesis, future price prediction;carbon price risk assessment modelling, Carbon trading, carbon trading; European Union Emissions Trading Scheme; stochastic field theory;Fractal Market Hypothesis; lyapunov exponent; evolutionary computing; future price prediction;carbon price risk assessment modelling, Future price prediction, stochastic field theory;Fractal Market Hypothesis, carbon price risk assessment modelling, Mathematics
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