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英文文献：Forecasting Financial Vulnerability in the US: A Factor Model Approach-预测美国的金融脆弱性:一种因子模型方法
英文文献作者：Hyeongwoo Kim,Wen Shi
英文文献摘要：
This paper presents a factor-based forecasting model for the financial market vulnerability, measured by changes in the Cleveland Financial Stress Index (CFSI). We estimate latent common factors via the method of the principal components from 170 monthly frequency macroeconomic data in order to out-of-sample forecast the CFSI. Our factor models outperform both the random walk and the autoregressive benchmark models in out-of-sample predictability at least for the short-term forecast horizons, which is a desirable feature since financial crises often come to a surprise realization. Interestingly, the first common factor, which plays a key role in predicting the financial vulnerability index, seems to be more closely related with real activity variables rather than nominal variables. We also present a binary choice version factor model that estimates the probability of the high stress regime successfully.
本文提出了一个基于因子的金融市场脆弱性预测模型，通过克利夫兰金融压力指数(CFSI)的变化来衡量。利用主成分法对170个月频次的宏观经济数据进行潜在公约数估计，从而对CFSI进行样本外预测。至少在短期预测范围内，我们的因子模型在样本外可预测性方面优于随机游走模型和自回归基准模型，这是一个可取的特征，因为金融危机经常出人意料地实现。有趣的是，在预测金融脆弱性指数中起关键作用的第一个公共因素，似乎与实际活动变量而非名义变量关系更密切。我们还提出了一个二元选择版本因子模型，成功地估计了高应力状态的概率。
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