The Framing Landscapes Model – Mathematical Modeling of Securities Analysts' Debates on Valuation at Extended Uncertainty

Joint work between Timo Ehrig and Louis H. Kauffman

This lecture discusses and demonstrates a model that maps debates. In a system theoretical perspective, the predictions of actors and mathematical models actors use to predict are part of the system that is attempted to be predicted. This insight gave rise to work in complex systems science to model stock market situations using inductive decision rules in computer simulations (Arthur/ Holland et al 1993). The framing landscapes model aims at mapping the logical/ cognitive structure of future estimates in real-world situations. Future estimates can only be declared as true/ false in hindsight and it is more precise to say that they were successful or failed, as they are performative and actively influence the future. The performative dimension of debates is core to the model that we present. This modeling is not at the level of quantitative models such as the Black-Scholes model, but rather at the level of making an image of on-going debates that have an effect on the evolution of the market itself. It begins in the web of uncertain and fluctuating propositions of the debate, takes a dynamic mathematical snapshot of this web, and allows the snapshot to evolve to extrema of a potential function that we call its fixed points. The snapshots and the results of its evolution then amplify and effect the original debate and give information about the structure of the market at that time. Our current work is on the mathematic foundations of the model and we did not yet test the model in an empirical setting, but we will present an outline of an empirical experiment that will follow soon.