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

Author

Listed:
  • 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,)

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.

Suggested Citation

  • Rialdi Azhar & Fajrin Satria Dwi Kesumah & Ambya Ambya & Febryan Kusuma Wisnu & Edwin Russel, 2020. "Application of Short-term Forecasting Models for Energy Entity Stock Price (Study on Indika Energi Tbk, JII)," International Journal of Energy Economics and Policy, Econjournals, vol. 10(1), pages 294-301.
    • Handle: RePEc:eco:journ2:2020-01-41
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    References listed on IDEAS

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    1. Aleksandra G. Polyakova & Seeram A. Ramakrishna & Vladimir V. Kolmakov & Dmitry V. Zavyalov, 2019. "A Model of Fuel and Energy Sector Contribution to Economic Growth," International Journal of Energy Economics and Policy, Econjournals, vol. 9(5), pages 25-31.
    2. Venus Khim-Sen Liew, 2004. "On Autoregressive Order Selection Criteria," Computational Economics 0404001, University Library of Munich, Germany.
    3. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    4. Erica Virginia & Josep Ginting & Faiz A.M. Elfaki, 2018. "Application of GARCH Model to Forecast Data and Volatility of Share Price of Energy (Study on Adaro Energy Tbk, LQ45)," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 131-140.
    5. Worawuth Kongsilp & Cesario Mateus, 2017. "Volatility risk and stock return predictability on global financial crises," China Finance Review International, Emerald Group Publishing Limited, vol. 7(1), pages 33-66, February.
    6. Warsono Warsono & Edwin Russel & Wamiliana Wamiliana & Widiarti Widiarti & Mustofa Usman, 2019. "Modeling and Forecasting by the Vector Autoregressive Moving Average Model for Export of Coal and Oil Data (Case Study from Indonesia over the Years 2002-2017)," International Journal of Energy Economics and Policy, Econjournals, vol. 9(4), pages 240-247.
    7. Warsono Warsono & Edwin Russels & Wamiliana Wamiliana & Widiarti Widiarti & Mustofa Usman, 2019. "Vector Autoregressive with Exogenous Variable Model and its Application in Modeling and Forecasting Energy Data: Case Study of PTBA and HRUM Energy," International Journal of Energy Economics and Policy, Econjournals, vol. 9(2), pages 390-398.
    8. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    Cited by:

    1. Ernie Hendrawaty & Rialdi Azhar & Fajrin Satria Dwi Kesumah & Sari Indah Oktanti Sembiring & Mega Metalia, 2021. "Modelling and Forecasting Crude Oil Prices during COVID-19 Pandemic," International Journal of Energy Economics and Policy, Econjournals, vol. 11(2), pages 149-154.
    2. Saring Suhendro & Mega Matalia & Sari Indah Oktanti Sembiring, 2021. "Public Sector Policy of Estimating Model for Renewable Energy," International Journal of Energy Economics and Policy, Econjournals, vol. 11(5), pages 609-613.
    3. Ambya Ambya & Toto Gunarto & Ernie Hendrawaty & Fajrin Satria Dwi Kesumah & Febryan Kusuma Wisnu, 2020. "Future Natural Gas Price Forecasting Model and Its Policy Implication," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 64-70.
    4. Toto Gunarto & Rialdi Azhar & Novita Tresiana & Supriyanto Supriyanto & Ayi Ahadiat, 2020. "Accurate Estimated Model of Volatility Crude Oil Price," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 228-233.

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    More about this item

    Keywords

    ARCH Effect; GARCH Model; Volatility; Share Price Forecasting; Investment Decision;
    All these keywords.

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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