Stock Price Forecasting Using the ARMA-GARCH Model

Abstract

The capital market plays a crucial role as a global economic indicator. This study aims to analyze the volatility and forecast the stock prices of PT Asuransi Tugu Pratama Indonesia using the ARMA-GARCH method with STATA application on stock price data from 2019 to 2023. The analysis process involves transforming the data into a time series, stationarity testing, ARCH-LM testing, and model evaluation using AIC criteria. The results indicate that the ARMA-GARCH method is effective with a low error rate of 9.61% (MAPE), providing accurate stock price forecasts to support investment decision-making. These findings offer insights into volatility dynamics and better investment strategies in the stock market.