Random Matrix Time Series

TL;DR

This paper introduces a novel time series model where coefficients are drawn from random matrix ensembles, providing theoretical foundations, estimation methods, and potential applications.

Contribution

It proposes a new class of time series models based on random matrix ensembles, including formal definitions, solutions, and statistical properties.

Findings

Derived theoretical solutions and statistical properties.

Discussed estimation and forecasting methodologies.

Suggested applications and connections to random matrix differential equations.

Abstract

In this paper, a time series model with coefficients that take values from random matrix ensembles is proposed. Formal definitions, theoretical solutions, and statistical properties are derived. Estimation and forecast methodologies for random matrix time series are discussed with examples. Random matrix differential equations and potential applications of the time series model are suggested at the end.