基于数据逻辑分析的主权债务评级模型重构
Reconstruction Rating Model of Sovereign Debt by Logical Analysis of Data
摘要：
评级机构提供的主权债务评级衡量一个国家的偿付能力，由贷款人或投资者衡量。它是投资所涉风险的一个指标，应正确和及时地加以确定。本文以布尔函数理论为基础，通过对数据的逻辑分析，重构主权债务评级。它根据世界银行为2012年至2015年期间确定的20个变量对国家进行分组。本文以全球三大评级机构之一的惠誉国际信用评级机构为案例进行研究。在探索评级方法、纠正机构的错误和确定其他未评级国家的估计评级方面，一种近似算法至关重要。结果是每年的决策树。每个国家都有一个评级。平均而言，该算法在训练集中达到了近98%的匹配率，并在测试集中得到了84%的验证。这是一个相当大的成就。
英文摘要：
Sovereign debt ratings provided by rating agencies measure the solvency of a country, as gauged by a lender or an investor. It is an indication of the risk involved in investment, and should be determined correctly and in a well timed manner. The present study reconstructs sovereign debt ratings through logical analysis of data, which is based on the theory of Boolean functions. It organizes groups of countries according to twenty World Bank defined variables for the period 2012 till 2015. The Fitch Rating Agency, one of the three big global rating agencies, is used as a case study. An approximate algorithm was crucial in exploring the rating method, in correcting the agencys errors, and in determining the estimated rating of otherwise non rated countries. The outcome was a decision tree for each year. Each country was assigned a rating. On average, the algorithm reached almost ninety eight percentage matched ratings in the training set, and was verified by eighty four percentage in the test set. This was a considerable achievement.
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。
