{"title":"好消息(坏消息)和知情交易的可能性:来自非法内幕交易的证据","authors":"Shunyu Su, Yezhou Sha","doi":"10.1080/1540496x.2023.2266111","DOIUrl":null,"url":null,"abstract":"ABSTRACTWe present a closed-form solution connecting the probability of informed trading (PIN) to the overlooked parameter that signaling private information is good or bad. Estimating PIN using illegal insider trading data, we find it sensitive to the certainty of positive private information in addition to the existed explanations, offering a new explanation for PIN‘s limitations in prior literature.KEYWORDS: Probability of informed tradingliquidityinformation asymmetryinsider tradingJEL: G12G14 AcknowledgmentsWe thank the editor Paresh Narayan, a subject editor and two reviewers for their comments. We also thank Tao Bing and Nianling Wang from Capital University of Economics and Business, as well as Cheng Yan from the University of Essex, for helpful discussions. We are grateful to Jaideep Oberoi from SOAS, University of London for providing the code estimating PIN with Bayesian approach. We are also indebted to the FinTech Lab of the School of Finance at Capital University of Economics and Business for providing High-Performance Computing (HPC) resources for large dataset estimation. This research is funded by Capital University of Economics and Business (Grant ID: QNTD202301). All errors are our own responsibility.Disclosure StatementNo potential conflict of interest was reported by the author(s).Additional informationFundingThe work was supported by the Capital University of Economics and Business [QNTD202301].","PeriodicalId":11693,"journal":{"name":"Emerging Markets Finance and Trade","volume":"61 4","pages":"0"},"PeriodicalIF":2.8000,"publicationDate":"2023-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Good (Bad) News and the Probability of Informed Trading: Evidence from Illegal Insider Trading\",\"authors\":\"Shunyu Su, Yezhou Sha\",\"doi\":\"10.1080/1540496x.2023.2266111\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACTWe present a closed-form solution connecting the probability of informed trading (PIN) to the overlooked parameter that signaling private information is good or bad. Estimating PIN using illegal insider trading data, we find it sensitive to the certainty of positive private information in addition to the existed explanations, offering a new explanation for PIN‘s limitations in prior literature.KEYWORDS: Probability of informed tradingliquidityinformation asymmetryinsider tradingJEL: G12G14 AcknowledgmentsWe thank the editor Paresh Narayan, a subject editor and two reviewers for their comments. We also thank Tao Bing and Nianling Wang from Capital University of Economics and Business, as well as Cheng Yan from the University of Essex, for helpful discussions. We are grateful to Jaideep Oberoi from SOAS, University of London for providing the code estimating PIN with Bayesian approach. We are also indebted to the FinTech Lab of the School of Finance at Capital University of Economics and Business for providing High-Performance Computing (HPC) resources for large dataset estimation. This research is funded by Capital University of Economics and Business (Grant ID: QNTD202301). All errors are our own responsibility.Disclosure StatementNo potential conflict of interest was reported by the author(s).Additional informationFundingThe work was supported by the Capital University of Economics and Business [QNTD202301].\",\"PeriodicalId\":11693,\"journal\":{\"name\":\"Emerging Markets Finance and Trade\",\"volume\":\"61 4\",\"pages\":\"0\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2023-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Emerging Markets Finance and Trade\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/1540496x.2023.2266111\",\"RegionNum\":3,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Emerging Markets Finance and Trade","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/1540496x.2023.2266111","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS","Score":null,"Total":0}
Good (Bad) News and the Probability of Informed Trading: Evidence from Illegal Insider Trading
ABSTRACTWe present a closed-form solution connecting the probability of informed trading (PIN) to the overlooked parameter that signaling private information is good or bad. Estimating PIN using illegal insider trading data, we find it sensitive to the certainty of positive private information in addition to the existed explanations, offering a new explanation for PIN‘s limitations in prior literature.KEYWORDS: Probability of informed tradingliquidityinformation asymmetryinsider tradingJEL: G12G14 AcknowledgmentsWe thank the editor Paresh Narayan, a subject editor and two reviewers for their comments. We also thank Tao Bing and Nianling Wang from Capital University of Economics and Business, as well as Cheng Yan from the University of Essex, for helpful discussions. We are grateful to Jaideep Oberoi from SOAS, University of London for providing the code estimating PIN with Bayesian approach. We are also indebted to the FinTech Lab of the School of Finance at Capital University of Economics and Business for providing High-Performance Computing (HPC) resources for large dataset estimation. This research is funded by Capital University of Economics and Business (Grant ID: QNTD202301). All errors are our own responsibility.Disclosure StatementNo potential conflict of interest was reported by the author(s).Additional informationFundingThe work was supported by the Capital University of Economics and Business [QNTD202301].
期刊介绍:
Emerging Markets Finance and Trade publishes research papers on financial and economic aspects of emerging economies. The journal features contributions that are policy oriented and interdisciplinary, employing sound econometric methods, using macro, micro, financial, institutional, and political economy data. Geographical coverage includes emerging market economies of Europe, the Balkans, the Middle East, Asia, Africa, and Latin America. Additionally, the journal will publish thematic issues and occasional special issues featuring selected research papers from major conferences worldwide.