基于支配性粗糙集方法的主权评级分析

IF 1.8 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Foundations of Computing and Decision Sciences Pub Date : 2020-03-01 DOI:10.2478/fcds-2020-0001
Ayrton Benedito Gaia do Couto, L. Gomes
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引用次数: 1

摘要

国际评级机构对风险进行分类的目的是在被评估国家履行其公共债务承诺的能力和处置方面指导投资者。在本研究中,在模糊和不确定的背景下,对主权评级的经济变量进行分析,通过遵循基于优势的粗糙集方法(DRSA)来推断模式(多标准规则)。发现数据中的模式可能有助于补贴各国的外国投资决策;该知识库可用于基于规则的专家系统(从训练示例中学习)。本研究旨在补充国际信用评级机构标准普尔(S&P)对2018年的分析。
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Sovereign Rating Analysis through the Dominance-Based Rough Set Approach
Abstract The classifications of risk made by international rating agencies aim at guiding investors when it comes to the capacity and disposition of the evaluated countries to honor their public debt commitments. In this study, the analysis of economic variables of sovereign rating, in a context of vagueness and uncertainty, leads the inference of patterns (multi-criteria rules) by following the Dominance-based Rough Set Approach (DRSA). The discovery of patterns in data may be useful for subsidizing foreign investment decisions in countries; and this knowledge base may be used in rule-based expert systems (learning from training examples).The present study seeks to complement the analysis produced by an international credit rating agency, Standard & Poor’s (S&P), for the year 2018.
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来源期刊
Foundations of Computing and Decision Sciences
Foundations of Computing and Decision Sciences COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
2.20
自引率
9.10%
发文量
16
审稿时长
29 weeks
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