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Indonesian Stock Market Volatility: GARCH Model

Author

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  • Endri Endri
  • Zaenal Abidin
  • Torang P. Simanjuntak
  • Immas Nurhayati

Abstract

The purpose of this paper is to examine the effect of macroeconom-ic variables (interest rates, inflation and exchange rates) and global stock exchanges (STI, SSE, N225, DJIA, FTSE100) on the movement of the Indonesian stock exchange (IHSG). The research data analy-sis method uses the GARCH model for time series data for the peri-od January 2012 to December 2018. The results show that the BI-rate, Inflation, Exchange Rate, Straits Times Index (STI), Shanghai Stock Exhange (SSE), Shanghai Stock Exhange (SSE), Nikkei 225 (N225)), Dow Jones Industrial Average (DJIA) and Financial Times Stock Exchange 100 (FTSE100) together have a significant effect on the IHSG. Partially shows the BI-rate, Inflation, and SSE have a sig-nificant negative influence, negative N225 is not significant, while the Exchange, STI, DJIA has a significant positive effect and FTSE100 has a non-significant positive effect on the IHSG.

Suggested Citation

  • Endri Endri & Zaenal Abidin & Torang P. Simanjuntak & Immas Nurhayati, 2020. "Indonesian Stock Market Volatility: GARCH Model," Montenegrin Journal of Economics, Economic Laboratory for Transition Research (ELIT), vol. 16(2), pages 7-17.
    • Handle: RePEc:mje:mjejnl:v:16:y:2020:i:2:7-17
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    References listed on IDEAS

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    2. Luh Putu Lila Wulandari & Anak Agung Sagung Sawitri & Andi Hermansyah, 2022. "The potential roles of pharmacy medication sales data to augment the syndromic surveillance system in response to COVID‐19 and preparedness for other future infectious disease outbreaks in Indonesia," International Journal of Health Planning and Management, Wiley Blackwell, vol. 37(1), pages 30-39, January.
    3. Yoonjae Noh & Jong-Min Kim & Soongoo Hong & Sangjin Kim, 2023. "Deep Learning Model for Multivariate High-Frequency Time-Series Data: Financial Market Index Prediction," Mathematics, MDPI, vol. 11(16), pages 1-18, August.
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    5. Lu, Linna & Lei, Yalin & Yang, Yang & Zheng, Haoqi & Wang, Wen & Meng, Yan & Meng, Chunhong & Zha, Liqiang, 2023. "Assessing nickel sector index volatility based on quantile regression for Garch and Egarch models: Evidence from the Chinese stock market 2018–2022," Resources Policy, Elsevier, vol. 82(C).
    6. Supriyanto Supriyanto & Suripto Suripto & Arif Sugiono & Putri Irmala Sari, 2021. "Impact of Oil Prices and Stock Returns: Evidence of Oil and Gas Mining Companies in Indonesia during the COVID-19 Period," International Journal of Energy Economics and Policy, Econjournals, vol. 11(4), pages 312-318.
    7. Endri Endri & M. Iqbal Rasyid Supeni & Yanti Budiasih & Matdio Siahaan & A. Razak & Sudjono Sudjono, 2021. "Oil Price and Leverage for Mining Sector Companies in Indonesia," International Journal of Energy Economics and Policy, Econjournals, vol. 11(4), pages 24-30.
    8. Endri Endri & Muhamad Rinaldi & Dini Arifian & Bungaran Saing & Aminudin Aminudin, 2021. "Oil Price and Stock Return: Evidence of Mining Companies in Indonesia," International Journal of Energy Economics and Policy, Econjournals, vol. 11(2), pages 110-114.
    9. Nagaraj Naik & Biju R. Mohan, 2021. "Stock Price Volatility Estimation Using Regime Switching Technique-Empirical Study on the Indian Stock Market," Mathematics, MDPI, vol. 9(14), pages 1-18, July.

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