The introduction of shelf registration in 1982 is used to examine the extent of price‐taking behavior among investment banks. Changes in underwriting syndicates are compared with the concomitant adjustment in underwriting spreads and management fees. The evidence is consistent with higher organizing costs and/or market power in the underwriting syndicate. Evidence on the components of the spreads and syndicate composition during the introduction of shelf registration is also presented.

The authors analyze a multiperiod model of trading with differentially informed traders, liquidity traders, and a marketmaker. Each informed trader's initial information is a noisy estimate of the long-term value of the asset and the different signals received by informed traders can have a variety of correlation structures. With this setup, informed traders not only compete with each other for trading profits, they also learn about other traders' signals from the observed order flow. The authors' work suggests that the initial correlation among the informed traders' signals has a significant effect on the informed traders' profits and the informativeness of prices.

Patterns in stock market trading volume, trading costs, and return volatility are examined using New York Stock Excha nge data from 1988. Intraday test results indicate that, for actively traded firms trading volume, adverse selection costs, and return volatility are higher in the first half-hour of the day. This eviden ce is inconsistent with the Admati and Pfleiderer (1988) model which predicts that trading costs are low when volume and return volatilit y are high. Interday test results show that, for actively traded firms , trading volume is low and adverse selection costs are high on Monday , which is consistent with the predictions of the Foster and Viswanath an (1990) model.

F. Douglas Foster, S. Viswanathan, Variations in Trading Volume, Return Volatility, and Trading Costs: Evidence on Recent Price Formation Models, The Journal of Finance, Vol. 48, No. 1 (Mar., 1993), pp. 187-211

The development of asset pricing models that rely on instrumental variables together with the increased availability of easily accessible economic time-series have renewed interest in predicting security returns. Evaluating the significance of these new research findings, however, is no easy task. Because these asset pricing theory tests are not independent, classical methods of assessing goodness-of-fit are inappropriate. This study investigates the distribution of the maximal R-square when k of m regressors are used to predict security returns. The authors provide a simple procedure that adjusts critical R-square values to account for selecting variables by searching among potential regressors.

We analyze a multi‐period model of trading with differentially informed traders, liquidity traders, and a market maker. Each informed trader's initial information is a noisy estimate of the long‐term value of the asset, and the different signals received by informed traders can have a variety of correlation structures. With this setup, informed traders not only compete with each other for trading profits, they also learn about other traders' signals from the observed order flow. Our work suggests that the initial correlation among the informed traders' signals has a significant effect on the informed traders' profits and the informativeness of prices.

We analyze a multi-period model of trading with differentially informed traders, liquidity traders, and a market maker. Each informed trader's initial information is a noisy estimate of the long-term value of the asset, and the different signals received by informed traders can have a variety of correlation structures. With this setup, informed traders not only compete with each other for trading profits, they also learn about other traders' signals from the observed order flow. Our work suggests that the initial correlation among the informed traders' signals has a significant effect on the informed traders' profits and the informativeness of prices.

Patterns in stock market trading volume, trading costs, and return volatility are examined using New York Stock Exchange data from 1988. Intraday test results indicate that, for actively traded firms trading volume, adverse selection costs, and return volatility are higher in the first half‐hour of the day. This evidence is inconsistent with the Admati and Pfleiderer (1988) model which predicts that trading costs are low when volume and return volatility are high. Interday test results show that, for actively traded firms, trading volume is low and adverse selection costs are high on Monday, which is consistent with the predictions of the Foster and Viswanathan (1990) model.

The development of asset pricing models that rely on instrumental variables together with the increased availability of easily‐accessible economic time‐series have renewed interest in predicting security returns. Evaluating the significance of these new research findings, however, is no easy task. Because these asset pricing theory tests are not independent, classical methods of assessing goodness‐of‐fit are inappropriate. This study investigates the distribution of the maximal when k of m regressors are used to predict security returns. We provide a simple procedure that adjusts critical values to account for selecting variables by searching among potential regressors.