Aug 2026· Advances in Economics, Management and Political Sciences· Vol 290, pp. 171-178· 0 citations
Abstract
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 explained from the perspective of dynamic conditional variance by GARCH models and their extensions. This paper first introduces the basic ideas of ARCH and GARCH models, with a focus on the issue of volatility clustering of financial returns. Then, it reviews the relevant research from three aspects: model evolution, application scenarios, and practical value. It also analyzes the role of GARCH-type models in capturing volatility persistence, asymmetric impact, and risk transmission through applications in cryptocurrencies, energy assets, and high-frequency financial data. The study shows that GARCH-type models capture the volatility clustering feature of financial returns well, but there is still room to improve the modeling of extreme risk, the handling of high-dimensional assets, and model interpretability.
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...
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· INTERNATIONAL JOURNAL OF APP...· 0 citations
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· International Journal of Man...· 0 citations
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...
Volatility is a fundamental characteristic of financial markets and plays a crucial role in investment decision-making, portfolio management, and financial risk assessment. Understanding the behaviour of stock market volatility is particularly important for frontier markets such as the Nepal Stock Exchange (NEPSE), whe...
