Forecasting and Financial Risk Analysis Using ARIMA Intervention Model: A Case Study on JMAS Tbk - Rina Yuliantika; Indah Gumala Andirasdini (Persatuan Aktuaris Indonesia, 2026)
The capital market is characterized by high volatility, making accurate forecasting and risk measurement essential for investment decision-making. This study aims to apply the Autoregressive Integrated Moving Average (ARIMA) intervention model and the Value at Risk (VaR) approach for stock prices forecasting and finansial risk analysis.The data consist of monthly stock prices of PT Asuransi Jiwa Syariah Jasa Mitra Abadi Tbk (JMAS) from January 2018 to December 2025. The ARIMA intervention model is applied to identify and quantify structural changes caused by external shocks, particularly the COVID-19 pandemic. The results indicate that the ARIMA (1,2,0) intervention model is the most appropriate model, with a step intervention function reflecting a sudden and permanent impact on stock price movements. The model satisfies diagnostic assumptions and demonstrates good forecasting accuracy, with a Mean Absolute Percentage Error (MAPE) of 13.01%. Forecasting results for January to March 2026 show that stock prices are expected to remain relatively low, indicating a slow post-pandemic recovery. Financial risk is measured using the Cornish-Fisher Value at Risk (VaR) approach at a 95% confidence level. The estimated VaR is -0.4245 indicating a maximum potential loss of 42.45% over a one-month period. This high level of risk reflects extreme market conditions during the COVID-19 period, which significantly increased volatility. This study contributes to financial analysis by integrating intervention-based time series modeling with risk measurement in a unified framework.