Public information, private information and microstructure theory [electronic resource].

Vega Martin, Clara.
127 p.
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In the first chapter, we present a new explanation for the post-announcement drift, i.e., the time-lag in market price adjustment to news surprises. Our explanation is that the post-announcement drift is a function of the private information agents have prior to news announcements. The more information people have about the "true" value of an asset---and the more they trade on this information---the smaller the abnormal return drift will be. We test this hypothesis empirically. Since private information is not observable by the econometrician, we use transaction-level data and a sequential trade microstructure model to calculate the probability of private information-base trading (PIBT) prior to an earnings announcement. We are able to show that a higher PIBT yields a lower post-announcement drift: the stocks with a low PIBT experience a drift that is 71% higher than high PIBT stocks. In the second chapter, we use a new dataset consisting of six years of real-time exchange rate quotations, macroeconomic expectations, and macroeconomic realizations (announcements), we characterize the conditional means of U.S. dollar spot exchange rates versus German Mark, British Pound, Japanese Yen, Swiss Franc, and the Euro. In particular, we find that announcement surprises (that is, divergences between expectations and realizations, or "news") produce conditional mean jumps; hence high-frequency exchange rate dynamics are linked to fundamentals. The details of the linkage are intriguing and include announcement timing and sign effects. The sign effect refers to the fact that the market reacts to news in an asymmetric fashion: bad news has greater impact than good news, which we relate to recent theoretical work on information processing and price discovery.
Source: Dissertation Abstracts International, Volume: 63-05, Section: A, page: 1926.
Supervisor: Francis X. Diebold.
Thesis (Ph.D.)--University of Pennsylvania, 2002.
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School code: 0175.
University of Pennsylvania.
Contained In:
Dissertation Abstracts International 63-05A.
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Restricted for use by site license.
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