The impact of insider trading on market efficiency and outsiders' welfare.
dc.contributor.author | George, Thomas John | |
dc.contributor.advisor | Bhattacharya, Sudipto | |
dc.contributor.advisor | Varian, Hal R. | |
dc.date.accessioned | 2020-09-09T03:30:11Z | |
dc.date.available | 2020-09-09T03:30:11Z | |
dc.date.issued | 1989 | |
dc.identifier.uri | https://hdl.handle.net/2027.42/162447 | |
dc.description.abstract | A mean-variance Noisy Rational Expectations Equilibrium model is extended to an economy in which traders have asymmetric opportunities for information acquisition. An application of the results is made to insider trading which predicts that insider trading enhances market efficiency even though it discourages outsiders from acquiring information. This result is shown to be generalizable to economies in which: (i) private and public information are substitutes, (ii) private information is not a Giffen good, and (iii) private information leaks into the public information set. A welfare analysis is presented which demonstrates that if insiders have a sufficiently large informational advantage, outsiders are better off if insiders are precluded from trading and a public release of information is made. In the context of the model, a method by which the precision of an insider's information can be inferred from observing his trading behavior is identified that does not rely on knowledge of the insider's preferences for risk. This method is used in conjunction with a measure of price informativeness to test the model's main predictions. Provided that cross-sectional differences in security related compensation are controlled for, the empirical results generally support the hypothesis that price informativeness is positively related to the quality of insiders' and outsiders' information. | |
dc.format.extent | 96 p. | |
dc.language | English | |
dc.title | The impact of insider trading on market efficiency and outsiders' welfare. | |
dc.type | Thesis | |
dc.description.thesisdegreename | PhD | en_US |
dc.description.thesisdegreediscipline | Finance | |
dc.description.thesisdegreegrantor | University of Michigan | |
dc.subject.hlbtoplevel | Business | |
dc.contributor.affiliationumcampus | Ann Arbor | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/162447/1/9013902.pdf | en_US |
dc.owningcollname | Dissertations and Theses (Ph.D. and Master's) |
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