Dynamic Analysis of the Relationship Between Market Sentiment and Stock Volatility at the Bei Using the Auto Regressive Integrated Moving Average (ARIMA) Model - Hariyanti; Rokhadi; Vena Vilenia (Dinasti Publisher, 2025)
This study aims to analyse the dynamic relationship between market sentiment and stock volatility on the Indonesia Stock Exchange (IDX) using the Autoregressive Integrated Moving Average (ARIMA) model. The research method used is a quantitative method with a causality approach using secondary data in the form of time series data of quarterly financial reports of PT Adhi Karya for the period 2008-2023, which is analysed through the ARIMA model for forecasting and selecting the best model based on statistical criteria. The ARIMA (1, 1, 1) model effectively represents the historical data pattern of quarterly assets of PT United Tractor with a stable trend and a slight gradual increase for the period December 2024 to December 2026. However, this model has limitations in capturing more complex variations or dynamics in the data. Accurate ARIMA models help maintain financial market stability, support efficient investment decision-making, and provide insights for macroeconomic policy planning that drives economic growth. In addition, reliable predictions increase investor confidence, both domestic and foreign, thereby strengthening financial sector risk management and encouraging investment for sustainable economic development.