ARIMA Model and Holt Winters Seasonal Smoothing Accuracy for Stock Price Prediction

Agus Sofian Eka Hidayat, Putu Darmawan

Abstract


One way to generate capital is by investments in the capital market, with the expectation that this money will increase in tandem with an issuer's stock price. In the past few decades, technology for communication and information has developed incredibly quickly, followed by the introduction of 5G, which boosts data transfer rates. This study intends to compare the accuracy of SARIMA and HOLTS WINTER SEASONAL SMOOTHING in predicting the price of TLKM. The SARIMA (1, 1, 1) x (0, 1, 1) 52 model outperforms Holt's Winter Seasonal Smoothing with a 3% MAPE in terms of forecasting TLKM stock price data

Keywords


forecasting; time series; Holt’s Winter Seasonal Smoothing; Seasonal ARIMA; TLKM

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References


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DOI: http://dx.doi.org/10.33021/jafrm.v2i1.4521

DOI (PDF): http://dx.doi.org/10.33021/jafrm.v2i1.4521.g1580

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