Double correlation model for operational risk: Evidence from Chinese commercial banks.

Abstract The Basel Accord requires commercial banks to meet a capital requirement for operational risk. Therefore, a reliable operational risk measurement is of great significance for financial institutions. In this paper, based on the framework of LDA, we propose a more appropriate model (Double Correlation model) in correlation structure construction, which considers both frequency correlation and mean severity correlation simultaneously. On this basis, annual loss scenarios for each risk cell are restored and VaR is also estimated by Monte Carlo simulation. Empirical study adopts the data of Chinese commercial banks disclosed to the public and contains the comparison of double correlation model and the other four correlation models. The result indicates that the VaR estimated by the double correlation model is significantly lower than that upon the assumption of comonotonicity, proving the existence of risk diversification. Meanwhile, the VaR estimated by double correlation model is significantly lower than that of the other two correlation models when confidence level is lower than 99% but the relationships between them will reverse if the confidence level rises to more than 99%. Highlights • We propose a double correlation model in operational risk modeling. • The model contains both frequency correlation and severity correlation. • We replace severity with mean severity in severity correlation construction. • We compare VaRs calculated by the double correlation model and other four models. [ABSTRACT FROM AUTHOR]