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All Journal Journal of Actuarial, Finance, and Risk Managment
Elisabeth Gloria Manurung
President University
Economics, Econometrics & Finance Mathematics

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Forecasting the Weekly Stock Price of PT. OCBC NISP Tbk. using Auto Regressive Integrated Moving Average Elisabeth Gloria Manurung; Edwin Setiawan Nugraha
Journal of Actuarial, Finance, and Risk Management Vol 2, No 2 (2023)
Publisher : Journal of Actuarial, Finance, and Risk Management

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33021/jafrm.v2i2.4812

Abstract

Stocks are widely used in financial markets and can be an option for companies seeking to raise funds. Additionally, investors often opt for stocks as an investment due to their potential for providing high returns. To aid investors in making informed decisions when buying and selling stocks and mitigating risks, professionals have developed different theories and analyses to forecast stock prices. Auto Regressive Integrated Moving Average (ARIMA) (p,d,q) technical analysis will be used in this study to predict the weekly stock price of PT Bank OCBC NISP Tbk (NISP.JK) for 7 weeks from Jan 7, 2022 to February 18, 2022. In this study, historical weekly stock price data for PT. Bank OCBC NISP Tbk (NISP.JK) from 1 January 2021, to 31 December 2021 was collected from Yahoo Finance website to create a forecast. The researches got 12 different ARIMA models, then the researcher determined that the second model (ARIMA (2,2,1) was the most effective. This model was chosen because it has second lowest AIC value and lowest MSE, RMSE, and MAE.
Co-Authors Edwin Setiawan Nugraha