F. Lima, Carolina Trinca Paulino, Rodrigo Lanna Franco Silveira, R. C. Gatsios, Alexandre Assaf Neto
{"title":"决定因素及其对公司和国家评级的影响","authors":"F. Lima, Carolina Trinca Paulino, Rodrigo Lanna Franco Silveira, R. C. Gatsios, Alexandre Assaf Neto","doi":"10.14421/ekbis.2022.6.1.1479","DOIUrl":null,"url":null,"abstract":"In the face of the latest world financial crises, the ratings released by the regulatory agencies have gained distinction in the financial market. This paper proposes models to predict the future ratings of companies and countries. The analysis was carried out using quarterly data from 2010 to 2018 from companies in Brazil, South Africa, Germany, Argentina, Australia, Canada, Chile, China, Colombia, South Korea, the United States, France, Italy, Japan, Mexico, Peru, the United Kingdom, Russia, and India. The sample's number of companies and countries is limited to the availability of rating information and the other model information. We use the panel-ordered logit model for classifying the rating and the other economic and financial variables as an independent. The results show that the financial and economic variables are essential to predict the rating of financial and non-financial companies in Brazil as well as the sovereign rating of the sample countries. The predictive capacity of the models reached values close to 80%, emphasizing the forecasts of large banks with 94% accuracy. For the country sample, the results are close to 80% accuracy. With the results of the research, improvement in the financial and economic indicators and the increase in the predictive capacity of the market agents for the prior determination of future ratings of financial companies are expected.","PeriodicalId":375939,"journal":{"name":"EkBis: Jurnal Ekonomi dan Bisnis","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Determining Factors and their Impacts on the Ratings of Companies and Countries\",\"authors\":\"F. Lima, Carolina Trinca Paulino, Rodrigo Lanna Franco Silveira, R. C. Gatsios, Alexandre Assaf Neto\",\"doi\":\"10.14421/ekbis.2022.6.1.1479\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the face of the latest world financial crises, the ratings released by the regulatory agencies have gained distinction in the financial market. This paper proposes models to predict the future ratings of companies and countries. The analysis was carried out using quarterly data from 2010 to 2018 from companies in Brazil, South Africa, Germany, Argentina, Australia, Canada, Chile, China, Colombia, South Korea, the United States, France, Italy, Japan, Mexico, Peru, the United Kingdom, Russia, and India. The sample's number of companies and countries is limited to the availability of rating information and the other model information. We use the panel-ordered logit model for classifying the rating and the other economic and financial variables as an independent. The results show that the financial and economic variables are essential to predict the rating of financial and non-financial companies in Brazil as well as the sovereign rating of the sample countries. The predictive capacity of the models reached values close to 80%, emphasizing the forecasts of large banks with 94% accuracy. For the country sample, the results are close to 80% accuracy. With the results of the research, improvement in the financial and economic indicators and the increase in the predictive capacity of the market agents for the prior determination of future ratings of financial companies are expected.\",\"PeriodicalId\":375939,\"journal\":{\"name\":\"EkBis: Jurnal Ekonomi dan Bisnis\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EkBis: Jurnal Ekonomi dan Bisnis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14421/ekbis.2022.6.1.1479\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EkBis: Jurnal Ekonomi dan Bisnis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14421/ekbis.2022.6.1.1479","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Determining Factors and their Impacts on the Ratings of Companies and Countries
In the face of the latest world financial crises, the ratings released by the regulatory agencies have gained distinction in the financial market. This paper proposes models to predict the future ratings of companies and countries. The analysis was carried out using quarterly data from 2010 to 2018 from companies in Brazil, South Africa, Germany, Argentina, Australia, Canada, Chile, China, Colombia, South Korea, the United States, France, Italy, Japan, Mexico, Peru, the United Kingdom, Russia, and India. The sample's number of companies and countries is limited to the availability of rating information and the other model information. We use the panel-ordered logit model for classifying the rating and the other economic and financial variables as an independent. The results show that the financial and economic variables are essential to predict the rating of financial and non-financial companies in Brazil as well as the sovereign rating of the sample countries. The predictive capacity of the models reached values close to 80%, emphasizing the forecasts of large banks with 94% accuracy. For the country sample, the results are close to 80% accuracy. With the results of the research, improvement in the financial and economic indicators and the increase in the predictive capacity of the market agents for the prior determination of future ratings of financial companies are expected.