{"title":"内幕交易与市场结构","authors":"Yesha Yadav","doi":"10.2139/SSRN.2652895","DOIUrl":null,"url":null,"abstract":"This Article argues that the emergence of algorithmic trading raises a new challenge for the law and policy of insider trading. It shows that securities markets comprise a cohort of algorithmic “structural insiders” that – by virtue of speed and physical proximity to exchanges – systematically gain first access to information and play an outsize role in price formation. This Article makes three contributions. First, it introduces and develops the concept of structural insider trading. Securities markets increasingly rely on automated traders utilizing algorithms – or pre-programmed electronic instructions – for trading. Policy allows traders to enjoy important structural advantages: (i) to physically locate on or next to an exchange, shortening the time it takes for information to travel to and from the marketplace; and (ii) to receive feeds of richly detailed data directly to these co-located trading operations. With algorithms sophisticated enough to respond instantly and independently to new information, co-located automated traders can receive and trade on not-fully-public information ahead of other investors. Secondly, this Article shows that structural insider trading exhibits harms that are substantially similar to those regulated under conventional theories of corporate insider trading. Structural insiders place other investors at a persistent informational disadvantage. Through their first sight of market-moving data, structural insiders can capture the best trades and erode the profits of informed traders, reducing their incentives to participate in the marketplace. Despite the similarity in harms, however, this Article shows that doctrine does not apply to restrict structural insider trading. Rather, structural insiders thrive in full view and with regulatory permission. Thirdly, the Article explores the implications of structural insider trading for the theory and doctrine of insider trading. It shows them to be increasingly incoherent in their application. In protecting investors against one set of insiders but not another, law and policy appear under profound strain in the face of innovative markets.","PeriodicalId":223837,"journal":{"name":"LSN: Criminal Law (Public Law - Crime) (Topic)","volume":"517 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Insider Trading and Market Structure\",\"authors\":\"Yesha Yadav\",\"doi\":\"10.2139/SSRN.2652895\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This Article argues that the emergence of algorithmic trading raises a new challenge for the law and policy of insider trading. It shows that securities markets comprise a cohort of algorithmic “structural insiders” that – by virtue of speed and physical proximity to exchanges – systematically gain first access to information and play an outsize role in price formation. This Article makes three contributions. First, it introduces and develops the concept of structural insider trading. Securities markets increasingly rely on automated traders utilizing algorithms – or pre-programmed electronic instructions – for trading. Policy allows traders to enjoy important structural advantages: (i) to physically locate on or next to an exchange, shortening the time it takes for information to travel to and from the marketplace; and (ii) to receive feeds of richly detailed data directly to these co-located trading operations. With algorithms sophisticated enough to respond instantly and independently to new information, co-located automated traders can receive and trade on not-fully-public information ahead of other investors. Secondly, this Article shows that structural insider trading exhibits harms that are substantially similar to those regulated under conventional theories of corporate insider trading. Structural insiders place other investors at a persistent informational disadvantage. Through their first sight of market-moving data, structural insiders can capture the best trades and erode the profits of informed traders, reducing their incentives to participate in the marketplace. Despite the similarity in harms, however, this Article shows that doctrine does not apply to restrict structural insider trading. Rather, structural insiders thrive in full view and with regulatory permission. Thirdly, the Article explores the implications of structural insider trading for the theory and doctrine of insider trading. It shows them to be increasingly incoherent in their application. In protecting investors against one set of insiders but not another, law and policy appear under profound strain in the face of innovative markets.\",\"PeriodicalId\":223837,\"journal\":{\"name\":\"LSN: Criminal Law (Public Law - Crime) (Topic)\",\"volume\":\"517 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-08-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"LSN: Criminal Law (Public Law - Crime) (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/SSRN.2652895\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"LSN: Criminal Law (Public Law - Crime) (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/SSRN.2652895","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This Article argues that the emergence of algorithmic trading raises a new challenge for the law and policy of insider trading. It shows that securities markets comprise a cohort of algorithmic “structural insiders” that – by virtue of speed and physical proximity to exchanges – systematically gain first access to information and play an outsize role in price formation. This Article makes three contributions. First, it introduces and develops the concept of structural insider trading. Securities markets increasingly rely on automated traders utilizing algorithms – or pre-programmed electronic instructions – for trading. Policy allows traders to enjoy important structural advantages: (i) to physically locate on or next to an exchange, shortening the time it takes for information to travel to and from the marketplace; and (ii) to receive feeds of richly detailed data directly to these co-located trading operations. With algorithms sophisticated enough to respond instantly and independently to new information, co-located automated traders can receive and trade on not-fully-public information ahead of other investors. Secondly, this Article shows that structural insider trading exhibits harms that are substantially similar to those regulated under conventional theories of corporate insider trading. Structural insiders place other investors at a persistent informational disadvantage. Through their first sight of market-moving data, structural insiders can capture the best trades and erode the profits of informed traders, reducing their incentives to participate in the marketplace. Despite the similarity in harms, however, this Article shows that doctrine does not apply to restrict structural insider trading. Rather, structural insiders thrive in full view and with regulatory permission. Thirdly, the Article explores the implications of structural insider trading for the theory and doctrine of insider trading. It shows them to be increasingly incoherent in their application. In protecting investors against one set of insiders but not another, law and policy appear under profound strain in the face of innovative markets.