Analisis Risiko Investasi Pasar Saham Syariah dengan Pendekatan Probabilistik pada Ketidakpastian Ekonomi

Alfi Maulana Rasyid, Elis Ratna Wulan

Abstract


This study analyzes investment risk using a probabilistic approach under conditions of economic uncertainty, using a case study of Islamic investment instruments in Indonesia. Using the Value at Risk (VaR) method based on Monte Carlo simulation and GARCH volatility modeling, this study evaluates Islamic stock portfolios for the period 2022-2025. The results show that the probabilistic approach is capable of estimating the maximum potential investment loss with good accuracy at the 95% confidence level, but has limitations in capturing extreme price movements at the 99% confidence level. The main contribution of this study is the integration of Islamic risk management principles into a modern probabilistic framework, which is novel in the existing literature. This study fills a research gap regarding the application of the probabilistic approach to Islamic investment instruments in emerging markets characterized by high volatility. The research findings provide important implications for Islamic investors and regulators in managing risk exposure amidst global economic uncertainty.


Keywords


risiko investasi, pendekatan probabilistik, ketidakpastian ekonomi

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References


Al Janabi, M. A. M. (2014). Analysis of market risk of Islamic and conventional portfolios and

Alahouel, F., & Loukil, N. (2024). An Islamic Inter-Temporal Capital Asset Pricing Model: Evidence From GCC Indexes. International Journal of Finance & Economics, 29(4), 4095-4112.

Billah, M., Alam, M. R., & Hoque, M. E. (2024). Global uncertainty and the spillover of tail risk between green and Islamic markets: A time-frequency domain approach with portfolio implications. International Review of Economics & Finance, 89, 1416-1433.

Burhanuddin. (2023). Investigating Volatility Behaviour: Empirical Evidence From Islamic Stock

Caldara, D., & Iacoviello, M. (2018). Measuring Geopolitical Risk. Board of Governors of the Federal Reserve System International Finance Discussion Papers, 1222.

Do they provide diversification benefits? Energy Economics, 107, 105845.

Forecasting and VaR-Risk Assessment. Barekeng: Jurnal Ilmu Matematika dan Terapan, 19(2), 1217-1236.

Hanif, M. (2011). Risk and Return Under Shari'a Framework: An Attempt to Develop Shari'a Compliant Asset Pricing Model (SCAPM). Pakistan Journal of Commerce and Social Sciences, 5(2), 283-292.

Husnan, S. (1996). Manajemen Keuangan: Teori dan Penerapan. Yogyakarta: BPFE.

Indices. Jurnal Ekonomi dan Bisnis, 26(1), 45-67.

insight. International Review of Financial Analysis, 74, 101669.

Irawan, W., Roy, M. I., Raya, F., Yakin, I. A., & Rustamunadi. (2026). Market Risk Measurement of Sharia Stock Portfolios Using Monte Carlo–Based Var: Evidence From An Indonesian Sharia Insurance Company. ISBANK: Jurnal Ekonomi dan Bisnis Islam, 8(1), 45-67.

Isnani, A., et al. (2025). Strengthening Syariah Financial Markets with GARCH-Based Stock Price

Knight, F. H. (1921). Risk, Uncertainty, and Profit. Boston: Houghton Mifflin Company.

Layaman, L., Wadud, A. M., Jaelani, A., & Mawaddah, Z. (2025). Macroeconomic Determinants of Islamic Stock Market Performance: An Analysis of Interest Rates, Inflation, Exchange Rates and Gold Prices. Lifalah: Jurnal Ekonomi dan Perbankan Syariah, 10(1), 1-20.

Lestari, P. A. (2024). Penerapan Value at Risk (VaR) Menggunakan Metode Variance-Covariance

Lin, L., & Su, Y. (2020). Oil price shocks and Islamic stock markets: Evidence from the MENA region. Emerging Markets Finance and Trade, 56(12), 2825-2842.

Maghyereh, A., Awartani, B., & Al Zoubi, T. (2022). Oil price volatility and Islamic stock markets:

Mufidah, N. P. (2025). Pengaruh Risiko Geopolitik dan Implied Volatility Minyak terhadap Imbal Hasil dan Volatilitas Indeks Saham Syariah Sektoral di Indonesia. Skripsi, Universitas Indonesia.

Nabi, G., Rehman, R. U., & Ali, R. (2025). Volatility Patterns of Islamic Equity Funds: Using Hybrid Machine Learning and GARCH Models. Journal of Statistical Sciences, 19(1), 45-78.

OJK. (2024). Statistik Perbankan Syariah 2023. Jakarta: Otoritas Jasa Keuangan.

Parametrik Historical dan Monte-Carlo dalam Penilaian Resiko Investasi Saham BEI Tahun 2022-2023. Artikel Ilmiah, Universitas Terbuka.

Sahroni, O. (2016). Maqashid Bisnis dan Investasi Syariah. Depok: Rajawali Pers.

Salisu, A. A., et al. (2022). Geopolitical risk and stock market volatility: A global perspective. International Review of Economics & Finance, 78, 234-251.

stock indices: Evidence from the Gulf Cooperation Council markets. International Journal of Islamic and Middle Eastern Finance and Management, 7(2), 210-227.

systematic review. Journal of Islamic Accounting and Business Research, 13(4), 589-612.

Tanin, T. I., Sarker, T., & Brooks, R. (2022). Information asymmetry and Islamic finance: A

Wang, X., Wu, C., & Xu, N. (2020). Geopolitical risk and stock market volatility: Global evidence. Finance Research Letters, 36, 101732.

Yang, C., & Yang, J. (2021). Geopolitical risk and stock market volatility: A new

Zahra, P., & Puspitasari, L. D. (2024). Value At Risk (VAR) Analysis using Historical and Monte Carlo Methods in Stock Prices of Bank CIMB Niaga, BSI, BJB, Bank Mega, and Bank Bukopin. International Journal of Global Operations Research, 5(2), 112-125.




DOI: https://doi.org/10.15548/jebi.v11i1.2475

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