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The mutual-information-based variance-covariance approach: an application to operational risk aggregation in Chinese banking

机译：基于互信息的方差-协方差方法：在中国银行业操作风险汇总中的应用

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摘要

Most advanced measurement approaches cannot simultaneously capture the overall dependence between operational risk components and be easy to use and understand. This paper proposes a mutual-information-based variance-covariance approach that is able to capture the overall correlation and is also highly tractable. Specifically, we replace the linear correlation coefficient with the global correlation coefficient in the framework of the variance-covariance approach. Originating from the theory of mutual information, the global correlation coefficient is able to capture both linear and nonlinear correlation relationships. The value-at-risk (VaR) of each individual risk component is calculated; these VaRs are then aggregated by using the global correlation coefficient. In empirical analysis, the proposed approach is employed to aggregate the operational risk of Chinese banking across business lines, based on the most comprehensive (to the best of our knowledge) operational risk data set. After an overall comparison with results from other correlation assumptions and the actual capital allocation of Chinese banking in 2013, we conclude that the actual capital allocation in China at present is not effective, and the aggregate VaR calculated from our approach is more reasonable.
机译：大多数高级度量方法无法同时捕获操作风险组件之间的整体依赖性，并且易于使用和理解。本文提出了一种基于互信息的方差-协方差方法，该方法能够捕获总体相关性并且也很容易处理。具体而言，我们在方差-协方差方法的框架内将线性相关系数替换为全局相关系数。起源于互信息理论，全局相关系数能够捕获线性和非线性相关关系。计算每个单独风险成分的风险价值（VaR）；然后，通过使用全局相关系数来汇总这些VaR。在实证分析中，基于最全面的（据我们所知）操作风险数据集，所提出的方法用于汇总各业务部门中的中国银行业的操作风险。在与其他相关假设的结果和2013年中国银行业的实际资本配置进行总体比较之后，我们得出结论，目前中国的实际资本配置并不有效，并且通过我们的方法计算出的总VaR更为合理。

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  • 来源
    《The Journal of Operational Risk》 |2014年第3期|3-19|共17页
  • 作者

    Jianping Li; Xiaoqian Zhu; Yongjia Xie; Jianming Chen; Lijun Gao; Jichuang Feng; Wujiang Shi;

  • 作者单位

    Institute of Policy and Management, Chinese Academy of Sciences, Beijing 100190, People's Republic of China;

    Institute of Policy and Management, Chinese Academy of Sciences, Beijing 100190, People's Republic of China and University of Chinese Academy of Sciences, Beijing 100190, People's Republic of China;

    Institute of Policy and Management, Chinese Academy of Sciences, Beijing 100190, People's Republic of China and University of Chinese Academy of Sciences, Beijing 100190, People's Republic of China;

    Institute of Policy and Management, Chinese Academy of Sciences, Beijing 100190, People's Republic of China;

    School of Business Administration, Shandong University of Finance and Economics, Jinan, Shandong 250014, People's Republic of China;

    Industrial Bank Co. Ltd, Fuzhou, Fujian 350003, People's Republic of China;

    GF Fund Management Co. Ltd, Guangzhou, Guangdong 510308, People's Republic of China;

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