Comparison between Holt Winter Additive and Holt Winter Multiplicative Methods in Forecasting Bank Central Asia (BBCA) Stock Price in Indonesia Stock Exchange - Alem Huga Martono; Ruben Clynton Oey; Sukono (Research Collaboration Community (RCC), 2026)
Stock market investment plays a pivotal role in the Indonesian economy as a source of capital formation and wealth creation for investors. As a financial instrument, the performance of stock markets is determined by the ability to predict future price movements accurately to minimize investment risks and maximize returns. Bank Central Asia (BBCA) is one of the largest private banks in Indonesia and is strategically positioned as one of the most actively traded and liquid stocks in the Indonesia Stock Exchange (IDX), consistently included in the LQ45 index. This research aims to determine the proper forecasting method for the existing data patterns of BBCA stock prices and to provide more accurate forecasting results for investment decision-making. The methods used include Holt Winter Additive and Holt Winter Multiplicative exponential smoothing techniques. The dataset comprises daily closing prices of BBCA stock from December 2, 2024, to December 5, 2025, totaling 241 trading days. From these two methods, the forecasting accuracy was evaluated using Mean Absolute Percentage Error (MAPE) and Mean Squared Error (MSE). The results show that the Holt Winter Additive method has the smallest MAPE value of 0.86% (MSE: 5,043.71) compared to the Holt Winter Multiplicative method with MAPE of 1.01% (MSE: 6,789.32), indicating that the Additive model provides superior forecasting performance for BBCA stock price prediction in the observed period.