Information Risk and Long-Run Performance of Initial Public Offerings [Paperback]

Frank Ecker examines the performance of U.S. initial public offerings (IPOs) from 1980 to 2002. He links positive and negative abnormal returns to the deviation of the realized information risk from the expected information risk. The author proposes effective measures for a long-term profitable investment strategy in IPOs.Exactly forty years after Eugene Famas (1965) article The Behavior of Stock Market Prices (Journal of Business), the play E?cient Capital Markets is still going strong. With his thesis, Frank Ecker is adding a new act to the play: His work is a combination of several new developments on the analytical and empirical capital market research front. Capital market e?ciency is based on two aspects. First, the ability of investors to identify a situation in which asset prices are out of the capital market equilibrium. Second, on the possibility of the market to make arbitrage pro?ts by driving the prices back to the equilibrium value. Both aspects are conditional on the set of relevant information. As a result, the basic question is: What is relevant information and how is it processed by investors? This work is building on the concept of information quality, information uncertainty or information risk. Famas e?cient market hypothesis is just a special case based on the assumption that new information is absolutely correct and completely credible to all investors. In contrast, this work makes use of the more general assumption that new information can be characterized by very di?erent degrees of credibility, or qu- ity. The setting of initial public o?erings is chosen as one of the few capital market transactions arguably characterized by high information asymmetry between the ?rms insiders (management) and outsiders (investors).and Motivation.- Valuation under Information Risk.- Derivation of a Returns-Based Measure of Information Quality.- Abnormal Returns Measurement and Hypotheses Development.- Tests with Abnormal Portfolio Returns.- RobustnlSd