Predicting (Economic) Trends: Why Signature Method in Machine Learning

Authors

Vladik Kreinovich, The University of Texas at El PasoFollow
Chon Van Le, International University of Ho-Chi-Minh CityFollow

Publication Date

8-1-2021

Comments

Technical Report: UTEP-CS-21-69

Abstract

In many practical situations, we can predict the trend -- i.e., how the system will change -- but we cannot predict the exact timing of this change: this timing may depend on many unpredictable factors. For example, we may be sure that the economy will recover, but how fast it will recover may depend on the status of the pandemic, on the weather-affected agriculture input, etc. In such trend predictions, one of the most efficient methods is signature method, which is based on applying machine learning techniques to several special characteristics of the corresponding time series. In this paper, we provide an explanation for the empirical success of the signature method.