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International Journal of Islamic Economics and Business Sustainability (IJIEBS)

Abstract

Background: This study investigates how sentiment related to the Palestine–Israel conflict influences volatility spillovers among selected Islamic equity markets. Methods – Weekly data on Islamic stock indices from seven major Muslim-majority countries (Indonesia, Nigeria, India, Pakistan, Bangladesh, and Turkey) are collected for the period 2013W1 through 2025W21. Geopolitical risk sentiment regarding the Palestine–Israel conflict is proxied by BlackRock’s conflict sentiment indicator. Volatility spillovers are measured via a Time-Varying Parameter VAR (TVP-VAR) joint connectedness framework. An Autoregressive Distributed Lag (ARDL) approach is then employed to assess the short-run and long-run impact of conflict sentiment (and energy price controls) on the TCI and on each country’s net spillover role. Results– Findings reveal that while Palestine–Israel sentiment does not significantly alter the aggregate TCI in the long run, it exerts significant and opposing long-run effects on specific markets: increased conflict-driven risk sentiment makes India’s Islamic market a stronger net receiver of volatility, whereas Indonesia’s market becomes a stronger net transmitter. Other markets (Bangladesh, Turkey, Iraq, Pakistan, Nigeria) show no robust long-run shifts.. Originality/value – This study uniquely integrates geopolitically derived sentiment from the Palestine–Israel conflict into a dynamic volatility spillover analysis for Islamic equity markets, employing a novel combination of TVP-VAR joint connectedness and ARDL methodologies.

References

Anand K, K., & Mishra, A. K. (2023). Market Connectedness and Volatility Spillovers: A Meta-Literature Review. Commodities, 2(3), 201–219. https://doi.org/10.3390/commodities2030013

Antonakakis, N., Chatziantoniou, I., & Gabauer, D. (2020). Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions. Journal of Risk and Financial Management, 13(4), 84. https://doi.org/10.3390/jrfm13040084

Apergis, N., & Fahmy, H. (2024). Geopolitical risk and energy price crash risk. Energy Economics, 140, 107975. https://doi.org/10.1016/j.eneco.2024.107975

Beckmann, J., Czudaj, R. L., & Arora, V. (2020). The relationship between oil prices and exchange rates: Revisiting theory and evidence. Energy Economics, 88, 104772. https://doi.org/10.1016/j.eneco.2020.104772

Caldara, D., & Iacoviello, M. (2018). Measuring Geopolitical Risk. International Finance Discussion Paper, 2018(1222), 1–66.

Chiţu, L., Ferrari Minesso, M., & Manu, A.-S. (2024). Speculation in oil and gas prices in times of geopolitical risks. Www.ecb.europa.eu. https://www.ecb.europa.eu/press/economic-bulletin/focus/2024/html/ecb.ebbox202402_01~b3d857ae05.en.html

Cui, J., & Maghyereh, A. (2024). Higher-order moment risk spillovers across various financial and commodity markets: Insights from the Israeli–Palestinian conflict. Finance Research Letters, 59, 104832. https://doi.org/10.1016/j.frl.2023.104832

Delle Foglie, A., & Panetta, I. C. (2020). Islamic stock market versus conventional: Are islamic investing a “Safe Haven” for investors? A systematic literature review. Pacific-Basin Finance Journal, 64, 101435. https://doi.org/10.1016/j.pacfin.2020.101435

Diebold, F. X., & Yılmaz, K. (2014). On the network topology of variance decompositions: Measuring the connectedness of financial firms. Journal of Econometrics, 182(1), 119–134. https://doi.org/10.1016/j.jeconom.2014.04.012

Diebold, F., Yilmaz, K., Binder, M., Dominguez, K., Frankel, J., Giavazzi, F., Leeper, E., & Reichlin, L. (2009). Journal compilation Ó Royal Economic Society. The Economic Journal, 119, 158–171. https://www.sas.upenn.edu/~fdiebold/papers/paper75/DY2final.pdf

Gajurel, D., & Chawla, A. (2022). International Information Spillovers and Asymmetric Volatility in South Asian Stock Markets. Journal of Risk and Financial Management, 15(10), 471. https://doi.org/10.3390/jrfm15100471

Ghaemi Asl, M., Rashidi, M. M., Tavakkoli, H. R., & Rezgui, H. (2024). Does Islamic investing modify portfolio performance? Time-varying optimization strategies for conventional and Shariah energy-ESG-utilities portfolio. The Quarterly Review of Economics and Finance, 94, 37–57. https://doi.org/10.1016/j.qref.2023.12.010

Guiso, L., Sapienza, P., & Zingales, L. (2003). People’s opium? Religion and economic attitudes. Journal of Monetary Economics, 50(1), 225–282. https://doi.org/10.1016/s0304-3932(02)00202-7

Hasyim, F., Ratnasari, R. T., Qomar, Moh. N., & Saleh, H. G. M. (2024). Resilience of Islamic and conventional stocks to geopolitical conflict: A GARCH model analysis. Asian Journal of Islamic Management (AJIM), 122–139. https://doi.org/10.20885/ajim.vol6.iss2.art4

Kazak, H., Saiti, B., Kılıç, C., Akcan, A. T., & Karataş, A. R. (2024). Impact of Global Risk Factors on the Islamic Stock Market: New Evidence from Wavelet Analysis. Computational Economics. https://doi.org/10.1007/s10614-024-10665-7

Kazouz, H., & Benammou, S. (2024). Volatility spillovers and time-varying correlations across stock and commodity markets: An assessment during the epidemic crisis era. Development and Sustainability in Economics and Finance, 2-4, 100024. https://doi.org/10.1016/j.dsef.2024.100024

Koop, G., Pesaran, M. Hashem., & Potter, S. M. (1996). Impulse response analysis in nonlinear multivariate models. Journal of Econometrics, 74(1), 119–147. https://doi.org/10.1016/0304-4076(95)01753-4

Lastrapes, W. D., & Wiesen, T. (2019). The Joint Spillover Index. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3454761

Lin, Z.-L., Ouyang, W.-P., & Yu, Q.-R. (2024). Risk spillover effects of the Israel-Hamas War on global financial and commodity markets: A time-frequency and network analysis. Finance Research Letters, 105618–105618. https://doi.org/10.1016/j.frl.2024.105618

Montel. (2024). Montel - Blog - How Does Political Instability Effect Energy Prices? Montel.energy. https://montel.energy/resources/blog/political-instability-effects-on-energy-prices

Pesaran, H. Hashem., & Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics Letters, 58(1), 17–29. https://doi.org/10.1016/s0165-1765(97)00214-0

Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds Testing Approaches to the Analysis of Level Relationships. Journal of Applied Econometrics, 16(3), 289–326. https://www.jstor.org/stable/2678547

Sahar, N. us, & Shah, A. (2017). Stock Market Return and Volatility Spillovers: The Case of Selected Muslim Majority Countries. Ssrn.com. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3180544

Setianingsih, H. E., Fauziyah, N., & Hasyim, F. (2024). Investor Sentiment and Stock Return Volatility: Implication of The Israel-Palestine Conflict on Sharia Stocks in Indonesia. Muslim Business and Economic Review, 3(2), 178–199. https://doi.org/10.56529/mber.v3i2.300

Stulz, R. M., & Williamson, R. (2003). Culture, openness, and finance. Journal of Financial Economics, 70(3), 313–349. https://doi.org/10.1016/s0304-405x(03)00173-9

Wang, B., Waris, M., Adamiak, K., Adnan, M., Hawkar Anwer Hamad, & Saad Mahmood Bhatti. (2024). The effects of the COVID-19 pandemic period on stock market return and volatility. Evidence from the Pakistan Stock Exchange. PloS One, 19(4), e0295853–e0295853. https://doi.org/10.1371/journal.pone.0295853

Yudaruddin, R., Lesmana, D., Yudaruddin, Y. A., Ekşi̇İ. H., & Başar, B. D. (2024). Impact of the Israel–Hamas conflict on financial markets of MENA region – a study on investors’ reaction. Journal of Economic and Administrative Sciences. https://doi.org/10.1108/jeas-04-2024-0104

Bahasa Abstract

Latar Belakang – Penelitian ini mengkaji bagaimana sentimen terkait konflik Palestina–Israel memengaruhi spillover volatilitas di antara pasar ekuitas syariah terpilih. Metode – Data mingguan pada indeks saham syariah dari tujuh negara dengan mayoritas Muslim (Indonesia, Nigeria, India, Pakistan, Bangladesh, dan Turki) dikumpulkan untuk periode 2013W1 hingga 2025W21. Sentimen risiko geopolitik terkait konflik Palestina–Israel diproksikan dengan indikator sentimen konflik BlackRock. Spillover volatilitas diukur menggunakan kerangka Time-Varying Parameter VAR (TVP-VAR) dengan pendekatan joint connectedness. Kemudian, pendekatan Autoregressive Distributed Lag (ARDL) digunakan untuk menilai dampak jangka pendek dan jangka panjang dari sentimen konflik (serta variabel kontrol harga energi) terhadap Total Connectedness Index (TCI) dan peran net spillover setiap negara. Hasil – Temuan menunjukkan bahwa meskipun sentimen Palestina–Israel tidak mengubah secara signifikan nilai agregat TCI dalam jangka panjang, sentimen konflik tersebut memiliki efek jangka panjang yang signifikan dan berlawanan di pasar tertentu: peningkatan sentimen risiko konflik membuat pasar syariah India menjadi penerima bersih volatilitas yang lebih kuat, sedangkan pasar Indonesia menjadi pemancar bersih volatilitas yang lebih kuat. Pasar lain (Bangladesh, Turki, Irak, Pakistan, Nigeria) tidak menunjukkan pergeseran jangka panjang yang kuat dalam peran net spillover. Novelty – Studi ini secara unik mengintegrasikan sentimen yang diturunkan dari konteks geopolitik konflik Palestina–Israel ke dalam analisis spillover volatilitas dinamis pada pasar ekuitas syariah, dengan menggunakan kombinasi metodologi TVP-VAR joint connectedness dan ARDL. Pendekatan ini menawarkan wawasan terkini tentang bagaimana peristiwa geopolitik yang memiliki resonansi religius membentuk baik integrasi sistemik maupun peran spillover spesifik negara dalam jaringan pasar yang saling terkait.

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