非平稳金融风险因素与英国宏观经济脆弱性
Non-stationary Financial Risk Factors and Macroeconomic Vulnerability for the UK
AI总结：
本文提出用非平稳因子模型度量金融压力，以捕捉尾部风险，并在英国数据上通过增长风险分析展示其优于传统平稳方法的优势。
摘要：
追踪金融脆弱性的累积是金融稳定政策的关键组成部分。由于金融系统的复杂性，这项任务十分艰巨，已有若干关于如何实现这一目标的提案。其中一种方式是通过构建能够为政策制定者提供信号的指数。尽管因子建模在金融和经济学中有着悠久的历史，但大多数应用往往侧重于平稳因子。然而，金融压力（尤其是尾部事件）可能表现出高度的惯性。本文主张摆脱平稳范式，转而提出将非平稳因子模型作为金融压力的度量。非平稳因子模型的关键优势在于，虽然一些流行的金融压力度量描述了金融压力指标的方差-协方差结构，但新指数能够捕捉分布的尾部。为展示这一点，我们将所获得的因子作为增长风险（growth-at-risk）分析中的变量。本文以英国金融市场为例，概述了如何构建金融压力的非平稳动态因子。
英文摘要：
Tracking the build-up of financial vulnerabilities is a key component of financial stability policy. Due to the complexity of the financial system, this task is daunting, and there have been several proposals on how to manage this goal. One way to do this is by the creation of indices that act as a signal for the policy maker. While factor modelling in finance and economics has a rich history, most of the applications tend to focus on stationary factors. Nevertheless, financial stress (and in particular tail events) can exhibit a high degree of inertia. This paper advocates moving away from the stationary paradigm and instead proposes non-stationary factor models as measures of financial stress. Key advantage of a non-stationary factor model is that while some popular measures of financial stress describe the variance-covariance structure of the financial stress indicators, the new index can capture the tails of the distribution. To showcase this, we use the obtained factors as variables in a growth-at-risk exercise. This paper offers an overview of how to construct non-stationary dynamic factors of financial stress using the UK financial market as an example.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
