Stability Study of Exponential Smooth Transition Double Autoregressive Model with Application

In this research, we propose a novel non-linear time series model referred to as the Exponential Smooth TransitionDouble Autoregressive Model of order p denoted as EXPSTDAR (p). This model is predicated on the double autoregressiveframework and incorporates an exponential function. Through the application of a local linearization technique, we derivea stability condition for a non-zero singular point of the model. And applying these conditions to the acquired models bymodeling real data that represents a weekly average closing price of Iron ore powder in dollars for the period from October2010 to May 2025 for several suggested orders of the model.

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Publication Details

Journal
Statistics, Optimization & Information Computing (University of Cambridge)
Published
2026-04-14
DOI
https://doi.org/10.19139/soic-2310-5070-3450
Primary Topic
Financial Risk and Volatility Modeling
Type
article
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article

Stability Study of Exponential Smooth Transition Double Autoregressive Model with Application

Azher Mohammad, Dler Abdulqader, Omar Mustafa
Statistics, Optimization & Information Computing (University of Cambridge)
Financial Risk and Volatility Modeling
article

Stability Study of Exponential Smooth Transition Double Autoregressive Model with Application

Azher Mohammad, Dler Abdulqader, Omar Mustafa
article en

Abstract

In this research, we propose a novel non-linear time series model referred to as the Exponential Smooth TransitionDouble Autoregressive Model of order p denoted as EXPSTDAR (p). This model is predicated on the double autoregressiveframework and incorporates an exponential function. Through the application of a local linearization technique, we derivea stability condition for a non-zero singular point of the model. And applying these conditions to the acquired models bymodeling real data that represents a weekly average closing price of Iron ore powder in dollars for the period from October2010 to May 2025 for several suggested orders of the model.

Statistics, Optimization & Information Computing (University of Cambridge)
University of Tikrit (IQ)
Openalex Percentile: Top 11%
Financial Risk and Volatility Modeling
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