{"title":"并购中的诉讼风险和债务融资成本","authors":"","doi":"10.1016/j.irfa.2024.103586","DOIUrl":null,"url":null,"abstract":"<div><div>In this paper, we use a semi-supervised machine learning technique, the <em>word2vec</em> word embedding model, to measure litigation risk for fixed-income issuers that use bond financing in primary market for mergers and acquisitions (M&As) in 28 countries. We investigate the relationship between the litigation risk and the offering yield of these securities, demonstrating that increased litigation risk increases financing costs. We analyze several ways to mitigate adverse effects, including the employment of more M&A advisors and assessing the legal environment in the issuing country. Our results are robust to an instrumental variable approach and alternative measures.</div></div>","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":null,"pages":null},"PeriodicalIF":7.5000,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Litigation risk and the cost of debt financing in M&As\",\"authors\":\"\",\"doi\":\"10.1016/j.irfa.2024.103586\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In this paper, we use a semi-supervised machine learning technique, the <em>word2vec</em> word embedding model, to measure litigation risk for fixed-income issuers that use bond financing in primary market for mergers and acquisitions (M&As) in 28 countries. We investigate the relationship between the litigation risk and the offering yield of these securities, demonstrating that increased litigation risk increases financing costs. We analyze several ways to mitigate adverse effects, including the employment of more M&A advisors and assessing the legal environment in the issuing country. Our results are robust to an instrumental variable approach and alternative measures.</div></div>\",\"PeriodicalId\":48226,\"journal\":{\"name\":\"International Review of Financial Analysis\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":7.5000,\"publicationDate\":\"2024-09-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Review of Financial Analysis\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1057521924005180\",\"RegionNum\":1,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Review of Financial Analysis","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1057521924005180","RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
Litigation risk and the cost of debt financing in M&As
In this paper, we use a semi-supervised machine learning technique, the word2vec word embedding model, to measure litigation risk for fixed-income issuers that use bond financing in primary market for mergers and acquisitions (M&As) in 28 countries. We investigate the relationship between the litigation risk and the offering yield of these securities, demonstrating that increased litigation risk increases financing costs. We analyze several ways to mitigate adverse effects, including the employment of more M&A advisors and assessing the legal environment in the issuing country. Our results are robust to an instrumental variable approach and alternative measures.
期刊介绍:
The International Review of Financial Analysis (IRFA) is an impartial refereed journal designed to serve as a platform for high-quality financial research. It welcomes a diverse range of financial research topics and maintains an unbiased selection process. While not limited to U.S.-centric subjects, IRFA, as its title suggests, is open to valuable research contributions from around the world.