For reliable insight. For informed decision making.
Mathematical Challenge January 2015 (PDF 400 kb)
The mean field theory is a well-established approximation method in physics, specifically in the field of complex many-body systems. One can imagine the mean field as a background field that effectively averages the interaction between individual particles.
We program highly scalable software for the systematic analysis of large amounts of complex data. Our insights are based on high resolution time-series analyses, state-of-the-art classification methods and user-friendly visualization. Fast algorithms and robust optimization allow consistent and transparent findings on the basis of repeatability and replicability. With Intelligent Technology, our clients strengthen their strategic advantage.
Recording non-linear dependencies
Identifying regime changes
Monitoring of instabilities
Informed decision making
Informed decision making requires reliable analyses, accurate forecasting and a continuously adjusted set of strategy options. We model dynamic systems for the simulation of diverse and comprehensive scenarios. Multivariate regressions, dynamic copula models and adaptive filters equipped with proprietary calibration methods provide the basis for consistent decision making. Our Intelligent Technology enables our clients to make more expedient and better informed decisions, staying ahead of the competition and safeguarding against the unexpected.
Dynamic system simulation
Pattern recognition for forecasting
Protection against extreme events