用最优共同资源和三并行两阶段动态 DEA 模型评估银行的风险管理效率

IF 1.9 4区经济学 Q2 ECONOMICS

Computational Economics Pub Date : 2024-07-22 DOI:10.1007/s10614-024-10682-6

Yun Tu, Bin Sheng, Chien-Heng Tu, Yung-ho Chiu

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引用次数: 0

摘要

将风险管理作为一个独立部门和可比因素，我们在银行中设立了三个平行部门（信贷、风险管理和投资）。为解决共同资源配置问题，本研究首次将三个平行部门结合起来，并在银行框架下进行了共同资源的优化配置。实证结果显示如下。(1）有风险管理的银行的效率和排名均优于无风险管理的银行。(2）以最优方式共享共同资源的银行比以非最优方式共享资源的银行效率更高。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Evaluating Bank Efficiency with Risk Management by Optimal Common Resource and Three-Parallel Two-Stage Dynamic DEA Model

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Evaluating Bank Efficiency with Risk Management by Optimal Common Resource and Three-Parallel Two-Stage Dynamic DEA Model

Taking risk management as an independent department and comparable factor, we set up three parallel departments (credit, risk management, and investment) in a bank. To resolve the problem of common resource allocation, this study is the first to combine the three parallel departments and the optimal common resource allocation in the banking framework. The empirical results show the following. (1) The efficiency and ranking of banks with risk management are better than that without risk management. (2) Banks that share common resources in an optimal way have higher efficiency than banks that share resources in a non-optimal way.

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来源期刊

Computational Economics MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-

CiteScore

4.00

自引率

15.00%

发文量

119

审稿时长

12 months

期刊介绍： Computational Economics, the official journal of the Society for Computational Economics, presents new research in a rapidly growing multidisciplinary field that uses advanced computing capabilities to understand and solve complex problems from all branches in economics. The topics of Computational Economics include computational methods in econometrics like filtering, bayesian and non-parametric approaches, markov processes and monte carlo simulation; agent based methods, machine learning, evolutionary algorithms, (neural) network modeling; computational aspects of dynamic systems, optimization, optimal control, games, equilibrium modeling; hardware and software developments, modeling languages, interfaces, symbolic processing, distributed and parallel processing