Estimation of the Parameters of Vector Autoregressive (VAR) Time Series Model with Symmetric Stable Noise

TL;DR

This paper introduces a new estimation method called FLOC for VAR models with symmetric stable noise, demonstrating its efficiency and accuracy through simulations.

Contribution

The paper presents the fractional lower order covariance (FLOC) method for estimating VAR model parameters with stable noise, a novel approach in this context.

Findings

FLOC method is efficient and accurate in simulations.

FLOC simplifies the estimation process for VAR models with stable noise.

Monte-Carlo simulations validate the proposed method.

Abstract

In this article, we propose the fractional lower order covariance method (FLOC) for estimating the parameters of vector autoregressive process (VAR) of order $p$, $p\geq 1$ with symmetric stable noise. Further, we show the efficiency, accuracy, and simplicity of our methods through Monte-Carlo simulation.