Studies on the Valuation of Credit Risk and Firm Value Considering Macroeconomic Variation

我们分析了业务变化对企业信用周期的影响，发现通过对宏观经济变量进行过滤分解而得到的包含趋势和周期项的模型，比包含原始变量的模型具有更高的违约预测能力。此外，我们开发了一个模型，将宏观压力情景转换为信用组合风险模型的风险参数，使用该模型，我们可以评估组合信用风险和公司价值，考虑宏观经济变量和行业之间的相关性。我们的研究成果发表在两个同行评审期刊上。

We analyzed the effect that business variation affects the credit cycle for companies, and found that a model with trend and cycle terms derived by a filtering decomposition of macroeconomic variables has more default predictive power than a model with original variables. In addition, we developed a model that transforms a macro-stress scenario into risk parameters of a credit portfolio risk model, the use of which enabled us to evaluate portfolio credit risk and firm-values, considering macroeconomic variables and correlations between industries. Our research outcomes are published in two peer-reviewed journals.