With our method and technology econometric systems can be modelled easy, scalable, and highly general. The analyst abstracts from sophisticated underlying mathematics and focusses on an intuitive system dynamical description of the econometric hypothesis.
Given historical data (time series), our software based on artificial intelligence (AI) and theory of nonlinear dynamic systems enables the conversion of such a hypothesis into a quantitative, empirical model. Doing so, the user is completely prevented from mathematical analysis and procedural programming. The models created this way are analysable in all details and also can be consumed by other software products and mathematical toolboxes.
This simplicity revolutionises the potential of econometric research. It, for instance, supports describing complex markets on just one notebook page or one screen slide, intuitively and with high explanatory power.
Since our models are created within a context of some general hypothesis, they are never mathematically cryptic or ulterior inscrutable. Everyone can understand with little effort their nature, their quantitative details, and their basic conditions under which they have been created.
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