Evaluation and Optimisation of Trading Strategies for EEX Financial Gas Futures on the TTF DA Market

BCI trades EEX Financial Gas Futures on the Title Transfer Facility Day-Ahead gas market on behalf of its clients. Traders manually trade based on experience and intuition. This is challenging due to the dynamic and volatile nature of the market. Therefore, BCI is interested in a systematic trading strategy which exploits the opportunities in the market. We determined our best trading strategy by applying a top-down approach. Here, we initially investigate the potential of existing strategies. Then, we make a selection for further development, backtesting, and optimisation. We realise this with the Backtesting.py library in Python, which meets all our criteria. Here, we optimise the strategies by maximising our defined objective function with grid search optimisation. We analyse the strategies based on multiple performance indicators, benchmarks, Walk-Forward Analyses, heatmaps, and quarterly results. These components construct a blueprint which explains how the most suitable strategy can be identified. Additionally, we test the strategies on the weak form of the Efficient Market Hypothesis (EMH). Based on the results, we conclude that the strategies outperform the market, suggesting that we reject the weak form of the EMH. Furthermore, with our blueprint, we conclude that the so-called EMA cross-over strategy is the most suitable.