英文标题：
《Pro-Cyclicality of Traditional Risk Measurements: Quantifying and
  Highlighting Factors at its Source》
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作者：
Marcel Br\\\"autigam, Michel Dacorogna, and Marie Kratz
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最新提交年份：
2019
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英文摘要：
  Since the introduction of risk-based solvency regulation, pro-cyclicality has been a subject of concerns from all market participants. Here, we lay down a methodology to evaluate the amount of pro-cyclicality in the way finnancial institutions measure risk, and identify factors explaining this pro-cyclical behavior. We introduce a new indicator based on the Sample Quantile Process (SQP, a dynamic generalization of Value-at-Risk), conditioned on realized volatility to quantify the pro-cyclicality, and evaluate its amount in the markets, considering 11 stock indices as realizations of the SQP. Then we determine two main factors explaining the pro-cyclicality: the clustering and return-to-the-mean of volatility, as it could have been anticipated but not quantified before, and, more surprisingly, the very way risk is measured, independently of this return-to-the-mean effect.
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中文摘要：
自引入基于风险的偿付能力监管以来，顺周期性一直是所有市场参与者关注的主题。在此，我们制定了一种方法，以评估芬兰机构衡量风险的方式中的顺周期性，并确定解释这种顺周期行为的因素。我们引入了一个基于样本分位数过程（SQP，风险价值的动态概括）的新指标，以实现的波动率为条件，量化顺周期性，并评估其在市场中的数量，考虑11个股票指数作为SQP的实现。然后，我们确定了解释顺周期性的两个主要因素：聚类和回归到波动率平均值，因为这本可以预测，但之前没有量化；更令人惊讶的是，风险的测量方式，独立于回归到平均值的影响。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Risk Management        风险管理
分类描述：Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
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