Predicting Value at Risk in Investment Portfolio Using Monte Carlo Simulation: The Case of The Syrian Internasional Islamic Bank

Abstract

This study applies a Monte Carlo simulation model to estimate the value at risk (VaR) for the Syrian International Islamic Bank's investment portfolio, aiming to assess potential risks and Information is provided for investment decisions making. Using 2024 portfolio data, the simulation, conducted with R-Studio, calculates the VaR to identify credit risks and guide strategic decision-making. The results indicate that the potential future loss for the portfolio may exceed the projected losses from individual loans. Based on these findings, the study recommends that the Bank reduce its funding in the near term to mitigate the identified risks. The research also emphasizes the importance of continuous monitoring of the portfolio to improve risk assessment practices over time. Furthermore, the study advocates for the integration of advanced modeling techniques and real-time data to strengthen the Bank's analytical capabilities. This would improve forecasting accuracy and enable more effective loan repricing strategies in response to changing financial conditions. The proactive adoption of these risk management tools is essential for the Bank to navigate the evolving financial landscape and remain resilient against market volatility. This research contributes to the broader discourse on financial risk management by providing actionable insights that can enhance the Bank's performance.