Application of Short-term Forecasting Models for Energy Entity Stock Price (Study on Indika Energi Tbk, JII)

Rialdi Azhar, Fajrin Satria Dwi Kesumah, Ambya Ambya, Febryan Kusuma Wisnu and Edwin Russel
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Rialdi Azhar: Faculty of Economics and Business, Universitas Lampung, Indonesia,
Fajrin Satria Dwi Kesumah: Faculty of Economics and Business, Universitas Lampung, Indonesia,
Ambya Ambya: Faculty of Economics and Business, Universitas Lampung, Indonesia,
Febryan Kusuma Wisnu: Faculty of Agriculture, Universitas Lampung, Indonesia.
Edwin Russel: Faculty of Economics and Business, Universitas Lampung, Indonesia,

International Journal of Energy Economics and Policy, 2020, vol. 10, issue 1, 294-301

Abstract: Share price as one kind of financial data is the time series data that indicates the level of fluctuations and heterogeneous variances called heteroscedasticity. The method that can be used to overcome the effect of autoregressive conditional heteroscedasticity (ARCH effect) is the GARCH model. This study aims to design the best model that can estimate the parameters, predict share price based on the best model and show its volatility. In addition, this paper discusses the prediction-based investment decision model. The findings indicate that the best model corresponding to the data is AR(4)-GARCH(1,1). The model is implemented to forecast the stock prices of Indika Energy Tbk, Indonesia, for 40 days and significantly presented good findings with an error percentage below the mean absolute.

Keywords: ARCH Effect; GARCH Model; Volatility; Share Price Forecasting; Investment Decision (search for similar items in EconPapers)
JEL-codes: C5 C53 Q4 Q47 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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