We compare two mechanisms for selling IPOs, the fixed price method and American book-building, when investors have correlated information and can observe each other's subscription decisions. In this environment, the fixed price method is a strategy that can create cascading demand. Alternatively, an underwriter building a book aggregates investor information into the offer price. We find that bookbuilding generates higher expected proceeds but exposes the issuer to greater uncertainty, and that it provides the option to sell additional shares that are not underpriced on the margin.

Using genetic programming techniques to find technical trading rules, we find strong evidence of economically significant out-of-sample excess returns to those rules for each of six exchange rates over the period 1981–1995. Further, when the dollar/Deutsche mark rules are allowed to determine trades in the other markets, there is significant improvement in performance in all cases, except for the Deutsche mark/yen. Betas calculated for the returns according to various benchmark portfolios provide no evidence that the returns to these rules are compensation for bearing systematic risk. Bootstrapping results on the dollar/Deutsche mark indicate that the trading rules detect patterns in the data that are not captured by standard statistical models.

The average relative profitability of different firms in the economy jumps erratically. Although investors are unable to observe these productivity switches, they continuously update their beliefs regarding high and low productivity firms by observing the total return on each firm, which consists of the average productivity plus noise. The portfolio choices, interest rate, and stock return processes are derived in a Cox-Ingersoll-Ross (1985a) style general equilibrium model. Three stylized facts of stock market returns are addressed: negative skewness, excess kurtosis, and predictive asymmetry (excess returns and future changes in volatility are negatively correlated). To measure the last stylized fact, an EGARCH model is fitted to sample paths simulated from the model. Parameter values that permit faster learning fit the three facts better.

This paper reexamines the explanatory power of beta, firm size, book-to-market equity, and the earnings-price ratio for average stock returns, correcting two currently controversial biases: selection bias in COMPUSTAT and the errors-in-variables (EIV) bias. After filling in the missing data on COMPUSTAT with the Moody's sample, I do not find any significantly different results for book-to-market equity from using the COMPUSTAT sample only. After correcting for the EIV bias, I find stronger support for the beta pricing theory than previous studies. Regardless of the presence of firm size, book-to-market equity, and earnings-price ratios, betas have significant explanatory power for average stock returns. In particular, firm size is barely significant using monthly returns, but no longer significant using quarterly returns. However, book-to-market equity still has significant explanatory power for average stock returns, even though the EIV bias is corrected.

This study examines the joint influence of board composition, leadership structure, and board ownership structure on the market's reaction to corporate antitakeover amendment proposals. The stock price reaction to antitakeover amendments is more negative when the board is dominated by inside and affiliated outside board members. Further, for firms in which the CEO also chairs the board, the reaction becomes increasingly negative as inside and affiliated outside board members increase their ownership stake in the firm and proportional representation on the board. In contrast, board composition and ownership structure have little power to explain the stock price reaction when the CEO does not chair the board. We conclude that monitoring by outside independent board members is important particularly when the CEO is also the board chair.

We examine stock price behavior in response to initial coverage, buy recommendations that are pre-released to important clients before the stock market opens, and find a strong positive valuation effect at the open. On average, it takes five minutes of trading for NYSE/AMEX stocks and 15 minutes for NASDAQ stocks to reflect the private information contained in these analyst recommendations, so when informational asymmetry is high, the centralized call market is more efficient than a competitive, but fragmented dealer market. Public news release leaves share prices unaltered. Overall, competition among informed traders causes private information to be rapidly incorporated into stock prices.

We extend the market microstructure literature by examining trading strategies of a small discretionary liquidity trader in call and continuous markets. Our investigation of trading strategies uses intraday market and limit orders, and introduces the market-at-open order as an alternative strategy for a small liquidity trader. We find that a small trader can reduce transaction costs by trading at the opening. Using tick-by-tick transaction data, we demonstrate that the market-at-open order consistently produces better prices than market and limit orders executed during the trading day.