Forecasting the Weekly Stock Prices of the Apple Inc. using the Autoregressive Integrated Moving Average

Novie Agustini Ongso

Abstract


Stocks have been the rising topic and popular investing instrument for many and chosen as an option for individuals and/or companies interested in potential high returns for their capital. Various theories and analyses have been developed to help individuals to forecast stock price. In this research, we will implement the Autoregressive Integrated Moving Average (ARIMA) to forecast the closing stock price of Apple Inc. (AAPL) from January 2023 to December 2023 with weekly intervals. The data yielded two different ARIMA models and the analysis shows that the (0,1,1) model is the most optimal, with MAPE of 2.28 %.

Keywords


ARIMA; Apple; forecasting; stock price

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References


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