STOCK PRICE MODELLING OF INDONESIAN BANKS: FORECASTING MODELLING

Date

2025-01-01

Author

Simarmata, Justin Eduardo
Weber, Gerhard Wilhelm
Baldemor, Milagros R.
Chrisinta, Debora

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Stock of banks in Indonesia are targeted for investors to invest in order to benefit from the distribution of dividends and capital gains. Proper observation is needed in selecting stocks as an investment place to avoid the risk of large losses. The aim of this study is to analyze the performance of portfolio optimization by forecasting the stocks of banks that are recommendations for investing. The stocks data used in the study comes from 2020 to 2023. The analysis process uses the R software, and the stocks data used includes BBCA.JK, BBNI.JK, BBRI.JK, BBTN.JK, and BMRI.JK. The forecasting methods used in this study include SES, DES, SMA, DMA, and ARIMA. The selection of the best method is based on the smallest values obtained from SSE, MSE, RMSE, and MAPE values. The best smoothing method to be used in forecasting is SES (α = 0.9) with Bank BCA, BNI, BRI, and BTN. In addition to using smoothing, stocks data forecasting is also carried out using the ARIMA method, where the best model tested is ARIMA(0, 1, 2) and is only found most precisely in Bank Mandiri’s stock data.

Subject Keywords

ARIMA, forecasting modelling, SES, Stock

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85217966432&origin=inward
https://hdl.handle.net/11511/113595

Collections

Graduate School of Applied Mathematics, Article