{"title":"疫情后时期的破产预测:以维谢格拉德集团国家为例","authors":"K. Valaskova, Dominika Gajdosikova, J. Bélas","doi":"10.24136/oc.2023.007","DOIUrl":null,"url":null,"abstract":"Research background: Effective monitoring of financial health is essential in the financial management of enterprises. Early studies to predict corporate bankruptcy were published at the beginning of the last century. The prediction models were developed with a significant delay even among the Visegrad group countries.\nPurpose of the article: The primary aim of this study is to create a model for predicting bankruptcy based on the financial information of 20,693 enterprises of all sectors that operated in the Visegrad group countries during the post-pandemic period (2020?2021) and identify significant predictors of bankruptcy. To reduce potential losses to shareholders, investors, and business partners brought on by the financial distress of enterprises, it is possible to use multiple discriminant analysis to build individual prediction models for each Visegrad group country and a complex model for the entire Visegrad group.\nMethods: A bankruptcy prediction model is developed using multiple discriminant analysis. Based on this model, prosperity is assessed using selected corporate financial indicators, which are assigned weights such that the difference between the average value calculated in the group of prosperous and non-prosperous enterprises is as large as possible.\nFindings & value added: The created models based on 6?14 financial indicators were developed using different predictor combinations and coefficients. For all Visegrad group countries, the best variable with the best discriminating power was the total indebtedness ratio, which was included in each developed model. These findings can be used also in other Central European countries where the economic development is similar to the analyzed countries. However, sufficient discriminant ability is required for the model to be used in practice, especially in the post-pandemic period, when the financial health and stability of enterprises is threatened by macroeconomic development and the performance and prediction ability of current bankruptcy prediction models may have decreased. Based on the results, the developed models have an overall discriminant ability greater than 88%, which may be relevant for academicians to conduct further empirical studies in this field.","PeriodicalId":46112,"journal":{"name":"Oeconomia Copernicana","volume":" ","pages":""},"PeriodicalIF":7.6000,"publicationDate":"2023-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Bankruptcy prediction in the post-pandemic period: A case study of Visegrad Group countries\",\"authors\":\"K. Valaskova, Dominika Gajdosikova, J. Bélas\",\"doi\":\"10.24136/oc.2023.007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Research background: Effective monitoring of financial health is essential in the financial management of enterprises. Early studies to predict corporate bankruptcy were published at the beginning of the last century. The prediction models were developed with a significant delay even among the Visegrad group countries.\\nPurpose of the article: The primary aim of this study is to create a model for predicting bankruptcy based on the financial information of 20,693 enterprises of all sectors that operated in the Visegrad group countries during the post-pandemic period (2020?2021) and identify significant predictors of bankruptcy. To reduce potential losses to shareholders, investors, and business partners brought on by the financial distress of enterprises, it is possible to use multiple discriminant analysis to build individual prediction models for each Visegrad group country and a complex model for the entire Visegrad group.\\nMethods: A bankruptcy prediction model is developed using multiple discriminant analysis. Based on this model, prosperity is assessed using selected corporate financial indicators, which are assigned weights such that the difference between the average value calculated in the group of prosperous and non-prosperous enterprises is as large as possible.\\nFindings & value added: The created models based on 6?14 financial indicators were developed using different predictor combinations and coefficients. For all Visegrad group countries, the best variable with the best discriminating power was the total indebtedness ratio, which was included in each developed model. These findings can be used also in other Central European countries where the economic development is similar to the analyzed countries. However, sufficient discriminant ability is required for the model to be used in practice, especially in the post-pandemic period, when the financial health and stability of enterprises is threatened by macroeconomic development and the performance and prediction ability of current bankruptcy prediction models may have decreased. Based on the results, the developed models have an overall discriminant ability greater than 88%, which may be relevant for academicians to conduct further empirical studies in this field.\",\"PeriodicalId\":46112,\"journal\":{\"name\":\"Oeconomia Copernicana\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":7.6000,\"publicationDate\":\"2023-03-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Oeconomia Copernicana\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.24136/oc.2023.007\",\"RegionNum\":1,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Oeconomia Copernicana","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.24136/oc.2023.007","RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Bankruptcy prediction in the post-pandemic period: A case study of Visegrad Group countries
Research background: Effective monitoring of financial health is essential in the financial management of enterprises. Early studies to predict corporate bankruptcy were published at the beginning of the last century. The prediction models were developed with a significant delay even among the Visegrad group countries.
Purpose of the article: The primary aim of this study is to create a model for predicting bankruptcy based on the financial information of 20,693 enterprises of all sectors that operated in the Visegrad group countries during the post-pandemic period (2020?2021) and identify significant predictors of bankruptcy. To reduce potential losses to shareholders, investors, and business partners brought on by the financial distress of enterprises, it is possible to use multiple discriminant analysis to build individual prediction models for each Visegrad group country and a complex model for the entire Visegrad group.
Methods: A bankruptcy prediction model is developed using multiple discriminant analysis. Based on this model, prosperity is assessed using selected corporate financial indicators, which are assigned weights such that the difference between the average value calculated in the group of prosperous and non-prosperous enterprises is as large as possible.
Findings & value added: The created models based on 6?14 financial indicators were developed using different predictor combinations and coefficients. For all Visegrad group countries, the best variable with the best discriminating power was the total indebtedness ratio, which was included in each developed model. These findings can be used also in other Central European countries where the economic development is similar to the analyzed countries. However, sufficient discriminant ability is required for the model to be used in practice, especially in the post-pandemic period, when the financial health and stability of enterprises is threatened by macroeconomic development and the performance and prediction ability of current bankruptcy prediction models may have decreased. Based on the results, the developed models have an overall discriminant ability greater than 88%, which may be relevant for academicians to conduct further empirical studies in this field.
期刊介绍:
The Oeconomia Copernicana is an academic quarterly journal aimed at academicians, economic policymakers, and students studying finance, accounting, management, and economics. It publishes academic articles on contemporary issues in economics, finance, banking, accounting, and management from various research perspectives. The journal's mission is to publish advanced theoretical and empirical research that contributes to the development of these disciplines and has practical relevance. The journal encourages the use of various research methods, including falsification of conventional understanding, theory building through inductive or qualitative research, first empirical testing of theories, meta-analysis with theoretical implications, constructive replication, and a combination of qualitative, quantitative, field, laboratory, and meta-analytic approaches. While the journal prioritizes comprehensive manuscripts that include methodological-based theoretical and empirical research with implications for policymaking, it also welcomes submissions focused solely on theory or methodology.