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Measuring credit risk and economic capital for commercial banks under non-Gaussian data
MU Wen-tao, CHEN Dian-fa, CHEN Ji
Systems Engineering - Theory & Practice ›› 2013, Vol. 33 ›› Issue (6) : 1372-1379.
PDF(1493 KB)
PDF(1493 KB)
Measuring credit risk and economic capital for commercial banks under non-Gaussian data
Measuring the credit risk and economic capital is one of the most important aims in risk management for commercial banks. The authors use Johnson transformation to solve the problem of economic capital under non-Gaussian data. By transforming real data to standard normal distribution, the authors overcome the restricts of Monte Carlo simulation in Copula method, which often requires the Gaussian or t distribution. It is convenient to simulate the correlated default time and the economic capital for banks. From the comparative analysis, the Johnson transformation is feasible and reasonable. This paper provides an effective quantitative method in risk management for commercial banks under "Basel Capital Accord" (Basel II) and the algorithm has a certain reference.
credit risk / Copula function / Johnson transformation / Monte Carlo simulation / economic capital {{custom_keyword}} /
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