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Volatility, information, and noise trading..作者:Danthine, Jean-Pierre1
Moresi, Serge2.
来源:European Economic Review; Jun93, Vol. 37 Issue 5, p961-982, 22p, 1 Diagram.
文献类型:Article.
主题语:*VOLATILITY (Finance)
*PRICES
*CAPITAL market
*EQUILIBRIUM (Economics)
*ECONOMICS.
摘要:We construct a dynamic competitive model where price volatility comes from both information arrival and noise trading. We first show that in the absence of noise, trading, there exists a fully revealing equilibrium, thus extending a well-known result to a multiperiod setting. Informational efficiency implies that price variations are serially uncorrelated and that volatility over time sums up to a constant. Thus a permanent increase in price volatility cannot be accounted for strictly in terms of an increase in information producing activities. In this context, information arrival at time 0 is welfare reducing (the Hirshleifer effect). We then study the effects of noise trading on the equilibrium prices. With noise trading, more information may mean less volatility as improved information places rational agents in a better position to counteract the actions of noise traders. We find that, in principle, significant episodes of noise trading can be identified as they translate into a negative correlation in price changes and that, under plausible hypotheses, more information is beneficiary in that it reduces the (net) welfare loss due to noise trading. [ABSTRACT FROM AUTHOR].
Copyright of European Economic Review is the property of Elsevier Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.).
作者单位:1University of Lausanne, Lausanne, Switzerland
2Georgetown University, Washington DC, USA.
ISSN:00142921.
入藏编号:11648059.
数据库: Business Source Complete.

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