Cutting Edge


We have developed a fully front to back platform, that is to say that it integrates all the stages of the management process, starting from

  • data analysis
  • backtesting
  • optimization of strategies thanks to evolutionary optimization tools that avoid over-learning
  • machine learning tools to improve strategies using other data sources
  • and finally, the fully automatic execution of trades taking into account risk limits

This completely turnkey platform is an extremely powerful tool for asset managers. They are able to enter their own strategies, test them and improve their decision process using latest machine learning techniques. The machine learning techniques are designed to detect a specific market environment, and adapt the strategies accordingly, rather than following explicit rules. Prediction is generated by analyzing large data sets from multiple sources, learning from previous trades and finding the best strategy depending on market conditions. Noise in the data is reduced by employing filtering and dimensionality reduction techniques. We have developed 3 state of the art machine learning methods that helps asset managers fine-tuning their investment decisions: -evolutionary optimization methods (swarm intelligence and Bayesian CMA ES o optimization) to find the best parameters in investment decisions -supervised learning methods based on decision-tree-based ensemble methods to classify the outcome of investment decisions -deep reinforcement learning methods to decide the best allocation between various strategies