Analysis of chaotic process forecast effectiveness based on terminal indicators of management quality

Abstract

This article is dedicated to analyzing the effectiveness of chaotic process forecasting techniques based on terminal indicators of management quality in the conditions of dynamic chaos, which is typical at electronic capital markets. We show the fundamental difference between trading asset observation series and probabilistic descriptions of traditional models based on the statistical paradigm. We consider an additive model with a chaotic systemic component and non-stationary noise, which describes the aforementioned observation series most adequately. Furthermore, we study the efficiency of conventional statistical solutions in the conditions of chaotic non-determinism