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首页> 外文期刊>The journal of risk finance >Prediction of bank failures in emerging financial markets: an ANN approach
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Prediction of bank failures in emerging financial markets: an ANN approach

机译：新兴金融市场中银行失败的预测：ANN方法

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Purpose - The recent financial crises in the world have brought attention to the need for a new international financial architecture which rests on crisis prevention, crisis prediction and crisis management. It is therefore both desirable and vital to explore new predictive techniques for providing early warnings to regulatory agencies. The purpose of this study is to propose a new technique to prevent future crises, with reference to the last banking crises in Turkey. Design/methodology/approach - ANN is utilized as an inductive algorithm in discovering predictive knowledge structures in financial data and used to explain previous bank failures in the Turkish banking sector as a special case of EFMs (emerging financial markets). Findings - The empirical results indicate that ANN is proved to differentiate patterns or trends in financial data. Most of the bank failures could be predicted long before, with the utilization of an ANN classification approach, but more importantly it could be proposed to detect early warning signals of potential failures, as in the case of the Turkish banking sector. Practical implications - The regulatory agencies could use ANN as an alternative method to predict and prevent future systemic banking crises in order to minimize the cost to the economy. Originality/value - This paper reveals that the ANN approach can be proposed as a promising method of evaluating financial conditions in terms of predictive accuracy, adaptability and robustness, and as an alternative early warning method that can be used along with the most common alternatives such as CAMEL, financial ratio and peer group analysis, comprehensive bank risk assessment, and econometric models.
机译：目的 - 世界上最近的金融危机引起了人们对新的国际金融体系结构的需求，该建筑基于预防危机，危机预测和危机管理。因此，探索为监管机构提供早期警告的新预测技术既需要且至关重要。这项研究的目的是提出一种新技术，以防止未来的危机，参考土耳其的最后一个银行危机。设计/方法/方法 - ANN在发现财务数据中的预测知识结构时被用作归纳算法，并用来解释土耳其银行业的先前银行失败，作为EFMS（新兴金融市场）的特殊情况。调查结果 - 经验结果表明，ANN被证明可以区分财务数据的模式或趋势。通过使用ANN分类方法，可以预测大多数银行的失败，但更重要的是，它可以发现它可以检测出潜在失败的预警信号，例如土耳其银行业。实际含义 - 监管机构可以使用ANN作为预测和防止未来全身银行危机的替代方法，以最大程度地减少经济成本。独创性/价值 - 本文揭示了可以将ANN方法作为一种有前途的方法来评估财务状况，以预测的准确性，适应性和鲁棒性以及可以与最常见的替代方案一起使用的替代性预警方法，例如作为骆驼，财务比率和同行小组分析，全面的银行风险评估和计量经济学模型。

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