英文标题：
《A copula based Markov Reward approach to the credit spread in European
Union》
---
作者：
Guglielmo D\'Amico, Filippo Petroni, Philippe Regnault, Stefania
Scocchera, Loriano Storchi
---
最新提交年份：
2019
---
英文摘要：
In this paper, we propose a methodology based on piece-wise homogeneous Markov chain for credit ratings and a multivariate model of the credit spreads to evaluate the financial risk in European Union (EU). Two main aspects are considered: how the financial risk is distributed among the European countries and how large is the value of the total risk. The first aspect is evaluated by means of the expected value of a dynamic entropy measure. The second one is solved by computing the evolution of the total credit spread over time. Moreover, the covariance between countries\' total spread allows understand any contagions in EU. The methodology is applied to real data of 24 countries for the three major agencies: Moody\'s, Standard and Poor\'s, and Fitch. Obtained results suggest that both the financial risk inequality and the value of the total risk increase over time at a different rate depending on the rating agency and that the dependence structure is characterized by a strong correlation between most of European countries.
---
中文摘要：
在本文中，我们提出了一种基于分段齐次马尔可夫链的信用评级方法和信用利差的多元模型来评估欧盟（EU）的金融风险。主要考虑两个方面：金融风险在欧洲国家之间的分布情况以及总风险的价值有多大。第一个方面通过动态熵测度的期望值进行评估。第二个问题通过计算总信用利差随时间的演变来解决。此外，各国总传播率之间的协方差可以了解欧盟的任何传染。该方法适用于穆迪、标准普尔和惠誉三大机构24个国家的实际数据。获得的结果表明，金融风险不平等和总风险值随时间以不同的速度增加，具体取决于评级机构，并且依赖结构的特点是大多数欧洲国家之间具有很强的相关性。
---
分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Computational Finance 计算金融学
分类描述：Computational methods, including Monte Carlo, PDE, lattice and other numerical methods with applications to financial modeling
计算方法，包括蒙特卡罗，偏微分方程，格子和其他数值方法，并应用于金融建模
--
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
--

---
PDF下载：
-->