On moving-average models with feedback

TL;DR

This paper investigates how feedback mechanisms in moving average models can alter their inherent short-memory property, revealing that feedback can cause these models to lose their characteristic short-term dependence.

Contribution

It demonstrates that feedback in moving average models can eliminate their short memory property, challenging traditional assumptions.

Findings

Feedback can cause moving average models to lose short memory.

Short memory property is not guaranteed in models with feedback.

Feedback alters the fundamental dynamics of moving average processes.

Abstract

Moving average models, linear or nonlinear, are characterized by their short memory. This paper shows that, in the presence of feedback in the dynamics, the above characteristic can disappear.