Macroeconomic Dynamics and Credit Risk: A Global Perspective
构建了一个框架，通过引入风险因子动态来建模条件损失分布，将信用组合的资产价值变化与全球宏观计量模型关联，从而分离宏观效应与异质性冲击。违约概率主要由企业受国内外商业周期的影响以及各国商业周期的联动性驱动。该模型能控制企业异质性，并在特定宏观经济情景下生成整个损失分布的多期预测。
We develop a framework for modeling conditional loss distributions through the introduction of risk factor dynamics. Asset value changes of a credit portfolio are linked to a dynamic global macroeconometric model, allowing macro effects to be isolated from idiosyncratic shocks. Default probabilities are driven primarily by how firms are tied to business cycles, both domestic and foreign, and how business cycles are linked across countries. The model is able to control for firm-specific heterogeneity as well as generate multi-period forecasts of the entire loss distribution, conditional on specific macroeconomic scenarios.