Quantitative Energy Trading Strategies
About Us
EEMM offers advanced trading strategies tailored to institutional energy producers, consumers and traders. Our team of energy experts, data scientists, and trading specialists leverage cutting-edge quantitative models to deliver optimal results for your unique trading needs. By combining the right approach with precise strategies, we ensure a competitive edge that drives superior performance outcomes. With a deep understanding of the complexities of energy markets, we are committed to securing long-term, sustainable returns on your investments.
Energy, Big Data, State-of-the-Art, Artificial Intelligence
Combined and applied to Europe’s leading energy markets
Our state-of-the-art quantitative strategies are based on mathematical models combined with algorithms and artificial intelligence. The models support both the quantity forecast for production or consumption and the trading algorithms in determining the optimum price point on the market. This process takes place through a complex elaboration and analysis of performance metrics of big data sets. In the case of weather data, this enables specific optimization of non-linear production forecasts. Furthermore, machine learning contributes to a multi-criteria improvement of dynamic and complex systems.
1
Input
The elaboration and analysis of performance metrics in big data sets such as weather data to optimize non-linear production and consumption forecast.
2
Method
Machine learning approach based on artificial intelligence techniques create the best possible trading strategy to find the optimum price point.
3
Output
Implementation of our adaptable advanced trading strategy on spot and forward markets.
EM² Analytics Terminal
The EEMM Analytics Terminal enhances volume forecasts by taking into account weather conditions, past performance and other market relevant factors. With the support of our specially developed trading algorithms, the EEMM Analytics Terminal, determines the price likely on the market for the corresponding zone. These processes are carried out through complex elaboration and analysis of performance metrics using Big Data methods. The results of this complex process are the so-called trading signals (EM² signals), which are then implemented on the market.
Production
Consumption
Emission Trading
Let's back test our strategy on your individual trading needs
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