Chaos theory in the prediction of Financial Markets

Abstract

We begin with a reflection and analysis of the nature of the problem of prediction in financial markets (Chorafas). In which his chaotic behavior stands out.

Currently, new prediction models are being tested in financial markets. The central objective is to improve the accuracy of forecasts in these markets.

Since 1960, with Lorenz, the study of problems whose behavior is sensitive to initial conditions, allowed the systematic development of chaos theory. Although its antecedents date back to past centuries, we currently find its applications in various fields of scientific work (Schifter).

Starting from a non-linear model (the logistic equation), we return to the analysis of Schifter, Braun and Talanquer to identify two types of regimes: the periodic (stable) and the chaotic. This model is useful because of its similarity to financial markets. With this exercise, we will know the relevant elements of chaos. A characteristic worth highlighting, and Braun demonstrates with this model, is that chaos has fractal properties.

Without a doubt, fractal models constitute one of the valuable supports for investigating the behavior of chaotic phenomena and thus being able to experiment with predictions in financial markets