W. Wong, Qiang Deng, M. Tseng, L. Lee, C. Hooy
{"title":"A stochastic Setting to Bank Financial Performance for Refining Efficiency estimates","authors":"W. Wong, Qiang Deng, M. Tseng, L. Lee, C. Hooy","doi":"10.1002/isaf.1357","DOIUrl":null,"url":null,"abstract":"This study contributes to develop a framework to measure the financial performance of banks in a stochastic setting. The framework comprises several steps, the first of which is the development of a financial performance measurement model to evaluate a bank's financial performance using a set of factors from the CAMEL Capital adequacy, Assets, Management Capability, Earning and Liquidity system. Second, the stochastic setting of the efficiency measurement is handled using the data collection budget allocation approach, whereby Monte Carlo simulations are used to analyse additional generated data and a genetic algorithm is used to refine the accuracy of the efficiency estimates. The results show that the accuracy of the model is greatly improved using the proposed approach. In contrast to the conventional deterministic model, the proposed framework is more useful to managers in determining the bank's future financial operations to improve the overall financial soundness of the bank. Copyright © 2014 John Wiley & Sons, Ltd.","PeriodicalId":153549,"journal":{"name":"Intell. Syst. Account. Finance Manag.","volume":"87 5","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Intell. Syst. Account. Finance Manag.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/isaf.1357","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
银行财务绩效的随机设定以改进效率估算
本研究有助于建立一个在随机环境下衡量银行财务绩效的框架。该框架包括几个步骤,第一步是开发一个财务绩效衡量模型,使用CAMEL资本充足率、资产、管理能力、收入和流动性系统中的一组因素来评估银行的财务绩效。其次,使用数据收集预算分配方法处理效率测量的随机设置,其中使用蒙特卡罗模拟来分析额外生成的数据,并使用遗传算法来改进效率估计的准确性。结果表明,该方法大大提高了模型的精度。与传统的确定性模型相比,所提出的框架对管理人员在确定银行未来的财务运营以提高银行的整体财务稳健性方面更有用。版权所有©2014 John Wiley & Sons, Ltd。
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