Generalized Weierstrass-Mandelbrot with Disturbance for Big Data Applications in Economic and Financial Systems

Disturbance such as COVID-19, pollution or policy variation to the economic and financial system has significant effect in the big data applications. Hence to study the effect of the disturbance on the related time series plays important role in further applying the big data in economic and financial system. Generalized Weierstrass-Mandelbrot Function is presented to study the complexity of the related time series theoretically and simultaneously. The results show that the disturbance indicated as the exponential form can generate multifractal features for the related time series. And the irregularity and long memory are also simulated by this model and described by the R/S method and multifractal analysis.