Predicting Stock Price Volatility Using ARCH-GARCH Models

Sabbar, Thijeel Odah

IJEFSD
Vol. 7 No. 4 (2025): International Journal on Economics, Finance and Sustainable Development (IJEFSD

This paper aims to apply ARCH-GARCH models to evaluate their ability to predict stock returns volatility in financial markets to help better allocate resources, manage risks, and improve investment decisions. This study was conducted on daily data of Apple Inc. stock prices during the period from January 2, 2024, to December 30, 2024, with 251 observations. The results indicate that ARCH-GARCH models provide good daily forecasts of stock price movements and are able to capture the fluctuation series by choosing the appropriate model for the prediction process. The ARCH(1) model was the most suitable for predicting the stock returns series of the study sample.