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Open access Sep 2026

The Role of Innovation Distributions in Forecasting Brent Crude Oil Volatility Using Univariate GARCH Models

This study investigates the impact of different error distributions on the performance of univariate GARCH-family models in modeling and forecasting the volatility of Brent crude oil returns from January 2014 to May 2025. Descriptive analysis reveals pronounced fluctuations, volatility clustering, and asymmetric beh...

Godsgift Chilaka Njoku · 0 citations
Review Open access Aug 2026

Analysis of Financial Return Volatility Clustering from a GARCH Perspective

The fluctuation characteristics of financial time series have always been one of the research hotspots in the academic community. Generally speaking, financial return series have the characteristics of volatility clustering, fat tails, conditional heteroskedasticity, asymmetric shocks, etc. The above phenomena can be e...

Dianjun Yang · 0 citations
Review Open access Aug 2026

Evolution of Statistical Methods in Financial Time Series Analysis: An Empirical Analysis from ARIMA to the GARCH Family of Models

Financial time series analysis is one of the key tools for asset pricing and forecasting, and its statistical methods have been continuously developing according to market demand. In the early days, the ARIMA model had great advantages in macro data analysis through its assumptions of linearity, homoscedasticity, and s...

Ruoxuan Shi · 0 citations
Open access Sep 2026

Linear and Nonlinear Econometric Models versus Machine-Learning Models: Evidence from Realized-Volatility Forecasting

A robust horizon-dependent ranking is revealed: Markov-switching HAR performs best at short horizons, ARFIMA generally leads at the monthly horizon, and the five-day horizon is intermediate, and forecast performance depends primarily on capturing the persistence and nonlinear dynamics most relevant at each horizon.

Rehim Kılıç · 0 citations
Open access Sep 2026

STOCK MARKET VOLATILITY MODELING WITH MACRO-FINANCIAL FACTORS: THE AR-X-GARCH APPROACH

The purpose of this study is to examine the dynamics of S&P 500 index volatility using daily data from January 1, 2020, to November 1, 2025. The analysis focuses on volatility persistence, clustering behavior, and the effects of the EUR/USD exchange rate and WTI crude oil prices on the stock market. For this purpose, d...

Süreyya Temelli · 0 citations
Open access Aug 2026

A COMPARATIVE ECONOMETRIC STUDY OF ARIMA-GARCH MODELS IN MODELING SAUDI ARAMCO STOCK VOLATILITY

This article examines the volatility dynamics of the daily adjusted closing prices of Saudi Aramco (SAOC) shares using a hybrid econometric framework that combines ARIMA and CS-GARCH models. Financial time series are typically characterized by volatility clustering, conditional heteroskedasticity, and asymmetric respon...

Ismail Hosni, Imane Said, Habiba Zanane et al. · 0 citations

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