For reliable insight. For informed decision making.
Mathematical Challenge August 2016 (PDF 398 kb)
Algorithmic Differentiation (AD), also known as Automatic Differentiation, is a set of programming techniques which allows to compute efficiently the sensitivities of a function with respect to its inputs.
Presentation by Prof. Dr. Michael Hengartner, President University of Zurich
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