Predicting Co-Movement of Banking Stocks Using Orthogonal GARCH

Apriani Dorkas Rambu Atahau, Robiyanto Robiyanto and Andrian Dolfriandra Huruta
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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

Risks, 2022, vol. 10, issue 8, 1-13

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.

Keywords: OGARCH; principal component analysis; state-owned enterprises; banking sector returns (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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