DOI: https://doi.org/10.14710/j.gauss.12.2.166-177

PEMODELAN DAN PREDIKSI HARGA SAHAM PERUSAHAAN FAST MOVING CUSTOMER GOODS MENGGUNAKAN VECTOR AUTOREGRESSIVE WITH EXOGENOUS VARIABLES (VARX)

*Marya Magdalena Simanjuntak  -  Departemen Statistika, Fakultas Sains dan Matematika, Undip, Indonesia
Tarno Tarno  -  Departemen Statistika, Fakultas Sains dan Matematika, Undip, Indonesia
Puspita Kartikasari  -  Departemen Statistika, Fakultas Sains dan Matematika, Undip, Indonesia
Open Access Copyright 2023 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract

The increase in the population of Indonesia causes consumption to increase. This has made the FMCG (Fast Moving Consumer Goods) industry in Indonesia grow rapidly and occupy the second largest proportion of market capitalization thereby attracting investors to invest. One way to choose the best stocks to invest is by modeling. Modeling is carried out on the share price of companies with large capitalization, namely Mayora Indah, Indofood CBP, and Siantar Top. One of the factors that influence a company's stock price is the stock price of a competitor, namely Unilever and Buyung Poetra. Therefore, to predict and determine the relationship between stocks, the VARX (Vector Autoregressive with Exogenous Variables) method is used. The data period in this study starts from January 4, 2021 to January 14, 2022 with the results of the analysis, namely VARX (1) is the model obtained for prediction. The errors from the model meet the white noise and multinormal assumptions. The SMAPE value of the Mayora, Indofood CBP, and Siantar Top variables is below 10% which means the model has very good predictive ability. In addition, the prediction results show that Indofood's share price is more stable than other stocks.

 

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Keywords: Stock; FMCG; VARX; SMAPE

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