使用ARIMA和指数式平滑技术建模和预测沙特银行稳定性

Abdulaziz Alnajjar¹, Hamzeh F Assous¹, Hazem Al-Najjar²

¹Department of Finance, School of Business, King Faisal University, Al-Ahsa, Saudi Arabia.

Frontiers in artificial intelligence

|March 12, 2026

概括

净利息收入和资本充足度等关键因素对沙特银行金融稳定有积极的影响. 然而,投资和贷款减值比率降低了稳定性,而GDP没有显著影响. 预测预测不同银行的不同结果.

科学领域:

金融经济学金融经济学
银行和金融业的银行和金融业.
计量经济学计量经济学

背景情况:

沙特银行的金融稳定对于经济增长至关重要.
了解关键绩效指标 (KPIs) 对于评估银行稳定性至关重要.
之前的研究已经通过不同的方法探索了影响银行稳定的因素.

研究的目的:

确定影响沙特银行的金融稳定性的关键因素,使用最佳的逐步线性回归模型.
开发Z-score预测到2030年的预测模型.
为利益相关者和监管机构提供见解,以支持沙特2030年愿景目标.

主要方法:

开发了一个最佳的逐步线性回归模型,使用来自11家沙特银行 (2014-2021) 的财务数据.
包括KPI如利能力,流动性,资产质量,资本化,银行规模和经济增长.
使用ARIMA和指数滑模型进行Z分数预测,并通过RMSE,MAE,MAPE和E-square进行验证.

主要成果:

最佳模型实现了最低的标准误差 (7.209) 和最高的调整R平方 (71.3%).
净利息收入 (NII1),资本充足率 (CAR) 和银行资产规模对稳定性产生积极影响.
投资比率和贷款减值比率对稳定性产生负面影响;GDP没有显著影响.

结论:

特定的金融比率和银行规模是沙特银行稳定的重要决定因素.
预测模型为未来的Z分数提供了洞察力,有助于战略规划.
调查结果支持监管机构和利益相关者加强与愿景2030相一致的金融稳定性.

关键词:

在ARIMA模型中,ARIMA模型是资产质量资产质量资产质量银行财富银行财富资本化的资本化.经济增长经济增长经济增长预测模型的预测模型.流动性的流动性流动性的流动性公司的利能力,利能力.

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