Pengaruh Indeks Harga Saham Gabungan (IHSG), Nilai Tukar, dan BI Rate terhadap Volatilitas Jakarta Islamic Index (JII)
DOI:
https://doi.org/10.62710/14xsvc61Keywords:
BI Rate, Indeks Harga Saham Gabungan, Jakarta Islamic Index, Nilai Tukar, VolatilitasAbstract
Jakarta Islamic Index (JII) merupakan indeks yang merepresentasikan kinerja saham syariah paling likuid di Indonesia. Meskipun demikian, penelitian mengenai pengaruh Indeks Harga Saham Gabungan (IHSG), nilai tukar rupiah terhadap dolar Amerika Serikat, dan BI Rate terhadap return serta mekanisme pembentukan volatilitas JII masih menunjukkan hasil yang beragam. Penelitian ini bertujuan menganalisis pengaruh IHSG, nilai tukar, dan BI Rate terhadap return Jakarta Islamic Index serta menjelaskan mekanisme pembentukan volatilitasnya menggunakan model Generalized Autoregressive Conditional Heteroskedasticity (GARCH) (1,1). Penelitian menggunakan pendekatan kuantitatif dengan rancangan eksplanatori berdasarkan data time series harian periode 3 Januari 2022–30 Desember 2025 sebanyak 959 observasi. Analisis dilakukan melalui statistik deskriptif, uji stasioneritas, estimasi mean equation, uji efek ARCH, estimasi GARCH (1,1), pemilihan distribusi residual, dan pengujian diagnostik model. Hasil penelitian menunjukkan bahwa IHSG berpengaruh positif dan signifikan terhadap return JII, sedangkan nilai tukar dan BI Rate tidak berpengaruh signifikan. Pada variance equation, parameter ARCH dan GARCH signifikan dengan tingkat volatility persistence yang tinggi, menunjukkan bahwa volatilitas JII terbentuk melalui interaksi shock jangka pendek dan volatilitas historis. Selain itu, distribusi Student's t memberikan spesifikasi model yang lebih baik dibandingkan distribusi Normal. Temuan ini memperkuat penerapan model GARCH (1,1) dalam menjelaskan mekanisme pembentukan return dan volatilitas pasar modal syariah Indonesia serta memberikan implikasi bagi investor dan regulator dalam pengelolaan risiko pasar.
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References
Andersen, T. G., Bollerslev, T., Diebold, F. X., & Labys, P. (2003). Modeling and forecasting realized volatility. Econometrica, 71(2), 579–625. https://doi.org/10.1111/1468-0262.00418
Basher, S. A., & Sadorsky, P. (2006). Oil price risk and emerging stock markets. Global Finance Journal, 17(2), 224–251. https://doi.org/10.1016/j.gfj.2006.04.001
Beik, I. S., & Fatmawati, S. W. (2014). Pengaruh indeks harga saham syariah internasional dan variabel makro ekonomi terhadap Jakarta Islamic Index. Al-Iqtishad: Jurnal Ilmu Ekonomi Syariah, 6(2), 155–178. https://doi.org/10.15408/aig.v6i2.1228
Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 31(3), 307–327. https://doi.org/10.1016/0304-4076(86)90063-1
Brooks, C. (2019). Introductory econometrics for finance (4th ed.). Cambridge University Press.
Christiansen, C., Schmeling, M., & Schrimpf, A. (2012). A comprehensive look at financial volatility prediction by economic variables. Journal of Applied Econometrics, 27(6), 956–977. https://doi.org/10.1002/jae.1274
Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). SAGE Publications.
Danila, N. (2023). Revisiting financial volatility in the Indonesian Islamic stock market: GARCH-MIDAS approach. Journal of Indonesian Economy and Business, 38(2), 166–177. https://doi.org/10.22146/jieb.v38i2.5704
Enders, W. (2014). Applied econometric time series (4th ed.). Wiley.
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
Engle, R. F. (2001). GARCH 101: The use of ARCH/GARCH models in applied econometrics. Journal of Economic Perspectives, 15(4), 157–168. https://doi.org/10.1257/jep.15.4.157
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
Gujarati, D. N., & Porter, D. C. (2009). Basic econometrics (5th ed.). McGraw-Hill.
Hasibuan, A. K., Pulungan, P. H., & Siregar, B. G. (2025). Pengaruh BI-Rate dan inflasi terhadap Indeks Harga Saham Jakarta Islamic Index di Bursa Efek Indonesia (BEI) periode 2020–2024. Jurnal Ekonomi, Akuntansi dan Manajemen Nusantara, 4(2), 200–207. https://doi.org/10.55338/jeama.v4i2.423
Majid, M. S. A. (2018). Assessing volatilities of monetary policy and their effects on the Islamic and conventional stock markets in Indonesia. Signifikan: Jurnal Ilmu Ekonomi, 7(2), 161–172. https://doi.org/10.15408/sjje.v7i2.7352
Mubarok, F. (2023). Volatility of Islamic stock market and exchange rate: Granger causality and GARCH approach. Journal of Innovation in Business and Economics, 7(1), 29–38. https://doi.org/10.22219/jibe.v7i01.23473
Mubarok, F., & Bisma, M. F. A. (2020). Modeling of Jakarta Islamic Index stock volatility return pattern with GARCH model. Al-Tijary, 6(1), 17–30. https://doi.org/10.21093/at.v6i1.2468
Otoritas Jasa Keuangan. (2023). Roadmap Pasar Modal Indonesia 2023–2027. Otoritas Jasa Keuangan.
Sugiyono. (2019). Metode penelitian kuantitatif, kualitatif, dan R&D. Alfabeta.
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