Measuring Cash Flow Sustainability Risks in Libyan Banks Using Random Models
Abstract
This study aimed to model cash flow sustainability risks in Libyan commercial banks within an environment characterized by "deep uncertainty" and "compound geopolitical shocks." The study addressed the limitations of traditional "Static Asset and Liability Management" (Static ALM) models in predicting the "sudden stop" phenomenon of cash flows due to their assumption of continuous linear growth, which fails to capture sudden changes in rentier environments. The study adopted an advanced econometric approach using "Stochastic Differential Equations" (SDEs) and the "Jump Diffusion Process" methodology. A computerized simulation system (SLS) was built using Python to apply the model to the quarterly financial data of Libyan banks during the structural transformation period (2024-2025). The results indicated that liquidity risks in Libya follow an "exponential" path rather than a linear one, confirming the failure of traditional models in estimating the timing of crises. The study also revealed the phenomenon of the "Defensive Liquidity Trap," statistically demonstrating that the impact of "structural dependency" on government and oil deposits outweighs the impact of "financial robustness." This renders massive reserves incapable of preventing liquidity depletion in the absence of efficient capital deployment. Furthermore, the comparison demonstrated the superiority of the proposed stochastic model in providing more accurate and conservative risk estimates through "risk smoothing," as opposed to the volatility observed in linear models. The study recommended adopting stochastic models in stress testing and diversifying deposit sources to decouple from sovereign fluctuations.
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