Commodity Price Dynamics and Islamic Stock Market Volatility in Indonesia

Authors

  • Hakiki Ramadhan Sunan Gunung Djati State Islamic University Bandung image/svg+xml Author
  • Muhammad Hasanuddin Sunan Gunung Djati State Islamic University Bandung image/svg+xml Author
  • Anisa Ilmia Sunan Gunung Djati State Islamic University Bandung image/svg+xml Author
  • Lidzikri Ahmad Syahru Rabbani International Islamic University, Islamabad image/svg+xml Author

DOI:

https://doi.org/10.22373/share.0079

Keywords:

Indonesian Sharia Stock Index (ISSI), Volatility Spillover, Geopolitical Risk, Commodity Prices, Exchange Rate

Abstract

Amid increasing integration between global commodity markets and emerging Islamic capital markets, understanding volatility transmission has become critical for risk management and policy design. This study investigates how volatility from Brent crude oil, gold, and crude palm oil (CPO) influences the Indonesian Sharia Stock Index (ISSI) from October 2022 to October 2024. The analysis uses daily data (N = 484) and employs GARCH and EGARCH frameworks to capture time-varying volatility, spillovers, and asymmetric responses to shocks. ARCH-LM tests confirm conditional heteroskedasticity in ISSI and USD/IDR returns, while EGARCH(1,1) models are also estimated for all variables to consistently account for asymmetry. Conditional volatility series are derived and examined to identify inter-market transmission effects. The results reveal that USD/IDR plays a dominant role, affecting gold negatively and CPO positively, reflecting the dual nature of commodities as safe-haven and export assets. Geopolitical risk significantly influences only Brent oil, suggesting a degree of insulation in Sharia equities. Strong leverage effects are observed in ISSI and CPO, where negative shocks amplify volatility more than positive ones, and CPO shows heavy-tail risk. Although commodity variables and geopolitical risk do not significantly explain ISSI returns, its volatility remains asymmetric, indicating stronger domestic drivers. These findings highlight the importance of exchange rate dynamics, asymmetric risk modeling, and commodity sensitivity in Islamic portfolio management, while offering implications for hedging strategies and macroprudential policy in open emerging economies.

ABSTRAK - Dinamika Harga Komoditas dan Volatilitas Pasar Saham Syariah di Indonesia. Seiring meningkatnya keterkaitan antara pasar komoditas global dan pasar modal syariah di negara berkembang, pemahaman tentang transmisi volatilitas menjadi semakin penting bagi pengelolaan risiko dan perumusan kebijakan. Studi ini menganalisis pengaruh volatilitas minyak Brent, emas, dan crude palm oil (CPO) terhadap Indeks Saham Syariah Indonesia (ISSI) selama periode Oktober 2022 hingga Oktober 2024. Dengan menggunakan data harian (N = 484), penelitian ini mengadopsi pendekatan GARCH dan EGARCH untuk menangkap dinamika volatilitas, efek spillover, serta respons asimetris terhadap guncangan pasar. Uji ARCH-LM menunjukkan adanya heteroskedastisitas bersyarat pada ISSI dan nilai tukar USD/IDR, sementara model EGARCH(1,1) digunakan secara konsisten untuk seluruh variabel guna mengakomodasi asimetri. Volatilitas kondisional yang dihasilkan kemudian dianalisis untuk mengidentifikasi transmisi antar pasar. Hasil menunjukkan bahwa USD/IDR menjadi faktor dominan dengan dampak negatif pada emas dan positif pada CPO, mencerminkan perbedaan peran komoditas sebagai aset lindung nilai dan komoditas ekspor. Risiko geopolitik hanya berpengaruh signifikan pada minyak Brent, mengindikasikan adanya ketahanan relatif pada pasar saham syariah. Efek leverage yang kuat ditemukan pada ISSI dan CPO, di mana berita buruk meningkatkan volatilitas secara lebih tajam, serta CPO menunjukkan risiko ekor yang tinggi. Meskipun variabel global tidak menjelaskan return ISSI secara signifikan, volatilitasnya tetap asimetris, menandakan peran faktor domestik. Temuan ini memberikan implikasi bagi manajemen portofolio syariah, strategi lindung nilai, dan kebijakan makroprudensial.

References

Adrian, M. A., & Rofiuddin, M. (2023). The US–China trade war in macroeconomic studies of the Indonesian Sharia Stock Index. Shirkah: Journal of Economics and Business, 8(3). https://doi.org/10.22515/shirkah.v8i3.538

Badan Pusat Statistik. (2023). Statistik kelapa sawit Indonesia 2023 (Indonesian palm oil statistics 2023). Badan Pusat Statistik. https://www.bps.go.id

Bakić, S. (2024). Impact of oil shocks on the oil, agricultural and food industry: Quantile and OLS regression. Ekonomika Poljoprivrede, 71(1), 293–308. https://doi.org/10.59267/ ekopolj2401293b

Bakshi, G., Gao, X., & Rossi, A. G. (2019). Understanding the sources of risk underlying the cross section of commodity returns. Management Science, 65(2), 619–641. https://doi.org/10.1287/mnsc.2017.2840

Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307–327. https://doi.org/10.1016/0304-4076(86)90063-1

Bollerslev, T., Chou, R. Y., & Kroner, K. F. (1992). ARCH modeling in finance: A review of the theory and empirical evidence. Journal of Econometrics, 52(1–2), 5–59. https://doi.org/10.1016/0304-4076(92)90064-X

Boungou, W., & Yatié, A. (2022). The impact of the Ukraine–Russia war on world stock market returns. Economics Letters, 215, Article 110516. https://doi.org/10.1016/j.econlet. 2022.110516

Caldara, D., & Iacoviello, M. (2018). Measuring geopolitical risk (International Finance Discussion Papers No. 1222). Board of Governors of the Federal Reserve System. https://doi.org/10.17016/IFDP.2018.1222

Cheong, C. W. (2009). Modeling and forecasting crude oil markets using ARCH-type models. Energy Policy, 37(6), 2346–2355. https://doi.org/10.1016/j.enpol.2009.02.026

Demiralay, S., & Kılınçarslan, E. (2019). The impact of geopolitical risks on travel and leisure stocks. Tourism Management, 75, 460–476. https://doi.org/10.1016/j.tourman.2019.06.013

Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007. https://doi.org/10.2307/ 1912773

Fama, E. F. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 25(2), 383–417. https://doi.org/10.2307/2325486

Francq, C., & Zakoïan, J.-M. (2004). Maximum likelihood estimation of pure GARCH and ARMA-GARCH processes. Bernoulli, 10(4), 605–637. https://doi.org/10.3150/bj/ 1093265632

Galloppo, G., & Paimanova, V. (2017). Efficiency and transparency effects on Eastern European financial markets. International Economics and Economic Policy, 14, 639–664. https://doi.org/10.1007/s10368-017-0372-8

Granger, C. W. J., & Newbold, P. (1974). Spurious regressions in econometrics. Journal of Econometrics, 2(2), 111–120. https://doi.org/10.1016/0304-4076(74)90034-7

Hansen, P. R., & Lunde, A. (2005). A forecast comparison of volatility models: Does anything beat a GARCH(1,1)? Journal of Applied Econometrics, 20(7), 873–889. https://doi.org/10.1002/jae.800

Hasyim, F., Ratnasari, R. T., Qomar, M. N., & Saleh, H. G. M. (2024). Resilience of Islamic and conventional stocks to geopolitical conflict: A GARCH model analysis. Asian Journal of Islamic Management, 6(2). https://doi.org/10.20885/ajim.vol6.iss2.art4

Hatemi-J, A. (2025). An asymmetric capital asset pricing model. Economia Internazionale/International Economics, 78(4), 675–686. https://doi.org/10.65644/EIIE. 078.04.0675

Ibrahim, A. (2024). Indonesian horizons in Islamic finance: Navigating risk, innovation, and social impact. Share: Jurnal Ekonomi dan Keuangan Islam, 13(1), vi–xi. https://doi.org/10.22373/share.v13i1.24266

Jain, S. (2021). Betas in the time of corona: A conditional CAPM approach using multivariate GARCH model for India. Managerial Finance, 48(3), 460–475. https://doi.org/10.1108/ MF-05-2021-0226

Jiang, M., & Kong, D. (2021). The impact of international crude oil prices on energy stock prices: Evidence from China. Energy Research Letters, 3(1). https://doi.org/10.46557/001c.28133

Kamri, N. A., Ramlan, S. F., & Ibrahim, A. (2014). Qurʾanic work ethics. Journal of Usuluddin, 40, 135–172. https://doi.org/10.22452/usuluddin.vol40.6

Kang, S. H., Kang, S. M., & Yoon, S. M. (2009). Forecasting volatility of crude oil markets. Energy Economics, 31(1), 119–125. https://doi.org/10.1016/j.eneco.2008.09.006

Kristyaningrum, A. C., & Hersugondo, H. (2021). The effect of oil price shock and inflation on stock returns: A comparative study on ASEAN-3. Jurnal Penelitian Ekonomi dan Bisnis, 6(1), 30–41. https://doi.org/10.33633/jpeb.v6i1.3950

Lucchetta, M. (2024). International aggregate risk: Effects on financial stability. Economics Letters, 238, Article 111773. https://doi.org/10.1016/j.econlet.2024.111773

Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77–91. https://doi.org/10.2307/2975974

Mestre, R. (2023). Stock profiling using time-frequency-varying systematic risk measure. Financial Innovation, 9(1). https://doi.org/10.1186/s40854-023-00457-7

Mezghani, T., Hamadou, F. B., & Abbes, M. B. (2021). The dynamic network connectedness and hedging strategies across stock markets and commodities: COVID-19 pandemic effect. Asia-Pacific Journal of Business Administration, 14(5), 626–645. https://doi.org/10.1108/ APJBA-01-2021-0036

Mulatsih, S. N., & Septiani, U. (2025). Unraveling the role of exchange rates: Bridging gold and oil prices to Indonesia’s Sharia stock index. El Dinar: Jurnal Keuangan dan Perbankan Syariah, 13(1). https://doi.org/10.18860/ed.v13i1.31714

Narayan, P. K., & Narayan, S. (2007). Modelling oil price volatility. Energy Policy, 35(12), 6549–6553. https://doi.org/10.1016/j.enpol.2007.07.020

Nawatmi, S., Nusantara, A., Maskur, A., & Setiawan, M. B. (2025). The influence of oil prices, gold prices, and inflation on the Indonesian Sharia stock index 2021–2025. International Journal of Multidisciplinary Sciences and Arts, 4(3). https://doi.org/10.47709/ijmdsa. v4i3.6439

Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica, 59(2), 347–370. https://doi.org/10.2307/2938260

Noval, N. (2022). Mediasi nilai tukar (IDR/USD) dalam pengaruh harga minyak mentah dan emas dunia terhadap pasar saham syariah di Indonesia. Jurnal Ilmu Ekonomi dan Bisnis Islam, 4(1), 42–56. https://doi.org/10.24239/jiebi.v4i1.89.42-56

Nugroho, I., Hidayatullah, M. S., & Jayanti, A. A. (2023). The effect of inflation, exchange rate, and BI rate on the Indonesian Sharia stock index. Journal of Islamic Economics and Finance Studies, 4(1). https://doi.org/10.47700/jiefes.v4i1.5804

Nunes, R. (2025). The efficient market hypothesis as an extension of neoclassical theory: A theoretical and empirical critique. Journal of Economics, Finance and Accounting Studies, 7(4). https://doi.org/10.32996/jefas.2025.7.4.10

Nusair, S. A., & Al-Khasawneh, J. A. (2023). Changes in oil price and economic policy uncertainty and the G7 stock returns: Evidence from asymmetric quantile regression analysis. Economic Change and Restructuring, 56, 2507–2536. https://doi.org/10.1007/ s10644-023-09494-9

Rahmah, S., Budiarti, R., & Purnaba, I. G. P. (2024). Analysis of the dependencies commodity prices and stock market indexes using copula. Barekeng: Jurnal Ilmu Matematika dan Terapan, 18(3), 1563–1572. https://doi.org/10.30598/barekengvol18iss3pp1563-1572

Rahmawati, E., & Nasrulloh, N. (2023). Increasing investment interest by strengthening Sharia compliance on the Indonesian stock exchange. Jurnal Ilmiah Manajemen Ekonomi & Akuntansi (MEA), 7(2). https://doi.org/10.31955/mea.v7i2.3077

Sampurna, D. S., & Maronrong, R. (2019). The effect of commodity price on Sharia stock markets volatility in developed and developing countries. In Proceedings of the 1st Asian Conference on Humanities, Industry, and Technology for Society. https://doi.org/10.2991/aicmar-18.2019.19

Sari, N., Ibrahim, A., Muzammil, M., & Muksal, M. (2024). Managing financing risk of Islamic banking products in Indonesia: A value at risk approach. Jurnal Ilmiah Islam Futura, 24(1), 213–240. https://doi.org/10.22373/jiif.v24i1.17693

Sen, A., Choudhury, K. D., & Datta, T. K. (2023). An analysis of crude oil prices in the last decade (2011–2020): With deep learning approach. PLOS ONE, 18(4). https://doi.org/10.1371/journal.pone.0268996

Supriani, I., Wicesa, N. A., & Tumewang, Y. K. (2024). Does COVID-19 cause structural changes in the Indonesian stock market behavior? A comparison of Islamic and conventional stock. Jurnal Ekonomi dan Bisnis Islam (Journal of Islamic Economics and Business), 10(1). https://doi.org/10.20473/jebis.v10i1.46353

Suryani, D., Fadhilla, M., & Labellapansa, A. (2022). Indonesian crude oil price (ICP) prediction using multiple linear regression algorithm. Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 6(6), 1047–1053. https://doi.org/10.29207/resti.v6i6.4590

Tiwari, A. K., Aye, G. C., Gupta, R., & Gkillas, K. (2020). Gold-oil dependence dynamics and the role of geopolitical risks: Evidence from a Markov-switching time-varying copula model. Energy Economics, 92, Article 104748. https://doi.org/10.1016/j.eneco.2020. 104748

Ülev, S., & Selçuk, M. (2022). Testing the weak-form market efficiency for the Islamic market indices: Evidence from Fourier wavelet ADF unit root test. Journal of Economic Policy Researches, 9(2), 579–602. https://doi.org/10.26650/JEPR1111585

White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838. https://doi.org/10.2307/1912934

Zahrok, F. F., Sulchan, M., Almira, D. T., & Aeni, E. A. N. (2021). Gold prices, world oil prices and large trade price index on Indonesian Sharia stock index with exchange value as a moderating variable in Indonesia. Indonesian Economic Review, 2(2). https://doi.org/10.53787/iconev.v2i2.12

Downloads

Published

05.06.2026

How to Cite

Ramadhan, H., Hasanuddin, M., Ilmia, A., & Rabbani, L. A. S. (2026). Commodity Price Dynamics and Islamic Stock Market Volatility in Indonesia. Share: Jurnal Ekonomi Dan Keuangan Islam, 15(1), 426-449. https://doi.org/10.22373/share.0079

Similar Articles

11-16 of 16

You may also start an advanced similarity search for this article.