基于行业相关性的银行业信用风险宏观压力测试研究

遵循宏观审慎管理的原则和理念, 提出了基于行业相关性的银行业信用风险宏观压力测试方法。通过考虑行业相关性和风险因子t分布特性, 对多元风险因子模型进行了拓展;将宏观压力测试情景与多元风险因子模型对接起来, 将压力情景下得到的行业景气指数取值转换为相应压力情景下行业风险因子的条件分布;在考察宏观经济周期的基础上, 采用指数平滑法、回归模型方法和历史情景分析方法处理宏观经济整个周期的历史数据, 从而确定宏观压力测试的情景设置, 这种情景设置能消除信用风险计量的顺周期性。这一过程将银行业经济资本管理与系统性风险防范有机地联系起来。这一信用风险宏观压力测试方法能反映不同行业信贷资产间的违约相关性, 能识别某一行业衰退对其他行业信贷资产产生的负面影响, 从而反映系统性风险的来源及其作用机理。

Research of Macro Stress Testing for Banking Credit Risk Based on the Industry Correlation

Following the principles and concepts of prudent macro management, a macro stress testing method for banking credit risk is put forward based on industry correlation. By considering industry correlation and the distribution characters of risk factor t, the multiple risk factor model is extended. The macro stress testing scenario with multiple risk factor model is considered, the values of industrial cycle index obtained under the stress scenario are transformed into conditional distributions of industrial risk factors under the corresponding scenario. Based on examination of macroeconomic cycle, the stress scenarios settings employ a variety of statistical methods to deal with historical macroeconomic data of the entire cycle in order to eliminate the procyclicality of credit risk measurement. The statistical methods include exponential smoothing, regression modeling approach and historical scenario analysis method. The process organically links the economic capital management with the prevention of systemic risk in banking industry. This macro stress testing method can reflect default correlations between credit assets in different industries, identify the negative impact on credit assets of other industries caused by some certain industry downturn, which reflects the source and mechanism of systemic risk.