Title: BANK CENTRAL ASIA (BCA) WEEKLY STOCK PRICE PREDICTION BASED ON FOURIER SERIES ESTIMATOR APPROACH
Authors: Mochamad Rasyid Aditya Putra, Sediono, M. Fariz Fadillah Mardianto, Elly Pusporani
Volume: 8
Issue: 12
Pages: 13-19
Publication Date: 2024/12/28
Abstract:
This study examines the Indonesian capital market, particularly Bank Central Asia (BCA) shares, as a vital investment instrument for economic growth. Fluctuations in BCA's share price are influenced by internal and external factors that often make it difficult for investors to make investment decisions. To predict BCA's stock price movements, a Fourier series estimator is used, which is effective in identifying recurring patterns in the data. With the latest data from January 2022 to November 2024, this study aims to provide an accurate prediction model, useful for investors, and assist banks in formulating long-term strategies, as well as supporting the achievement of Sustainable Development Goals (SDGs) point 8 regarding Decent Work and Economic Growth. The results showed that the Fourier series estimator produced an optimal oscillation parameter value (?) of 17. The estimated model formed produced an MSE value of 3784.379, a MAPE value of 0.5249203%, and an R-Square value of 97.7224% which was classified as highly accurate prediction results, because the MAPE value was less than 10%.