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Predicting Co-Movement of Banking Stocks Using Orthogonal GARCH

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  • Apriani Dorkas Rambu Atahau

    (Department of Management, Satya Wacana Christian University, Salatiga 50711, Indonesia)

  • Robiyanto Robiyanto

    (Department of Management, Satya Wacana Christian University, Salatiga 50711, Indonesia)

  • Andrian Dolfriandra Huruta

    (Department of Economics, Satya Wacana Christian University, Salatiga 50711, Indonesia)

Abstract

This study investigates the application of orthogonal generalized auto-regressive conditional heteroscedasticity (OGARCH) in predicting the co-movement of banking sector stocks in Indonesia. All state-owned banking sector stocks in Indonesia were studied using daily data from January 2013 to December 2019. The findings indicate that the OGARCH method can simplify the covariance matrix. Most state-owned banking stocks in the banking sector have a similar principal component influencing their conditional variance. Nonetheless, one stock has different principal components. The findings imply that combining the state-owned banking stocks with different principal components effectively reduces the risk of state-owned banking stock portfolios.

Suggested Citation

  • Apriani Dorkas Rambu Atahau & Robiyanto Robiyanto & Andrian Dolfriandra Huruta, 2022. "Predicting Co-Movement of Banking Stocks Using Orthogonal GARCH," Risks, MDPI, vol. 10(8), pages 1-13, August.
  • Handle: RePEc:gam:jrisks:v:10:y:2022:i:8:p:158-:d:878664
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    References listed on IDEAS

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    1. Koulakiotis, Athanasios & Kartalis, Nikos & Lyroudi, Katerina & Papasyriopoulos, Nicholas, 2012. "Asymmetric and threshold effects on comovements among Germanic cross-listed equities," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 327-342.
    2. Luo, Cuicui & Seco, Luis & Wu, Lin-Liang Bill, 2015. "Portfolio optimization in hedge funds by OGARCH and Markov Switching Model," Omega, Elsevier, vol. 57(PA), pages 34-39.
    3. Arindam Bandyopadhyay & Sonali Ganguly, 2012. "Empirical estimation of default and asset correlation of large corporates and banks in India," Journal of Risk Finance, Emerald Group Publishing, vol. 14(1), pages 87-99, December.
    4. El Hedi Arouri, Mohamed & Lahiani, Amine & Nguyen, Duc Khuong, 2015. "World gold prices and stock returns in China: Insights for hedging and diversification strategies," Economic Modelling, Elsevier, vol. 44(C), pages 273-282.
    5. Leeves, Gareth, 2007. "Asymmetric volatility of stock returns during the Asian crisis: Evidence from Indonesia," International Review of Economics & Finance, Elsevier, vol. 16(2), pages 272-286.
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    Cited by:

    1. Apriani Dorkas Rambu Atahau & Robiyanto Robiyanto & Andrian Dolfriandra Huruta, 2023. "Co-Movement of Indonesian State-Owned Enterprise Stocks," Economies, MDPI, vol. 11(2), pages 1-24, February.

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