A price barrier is a price level at which a large number of investors either buy or sell securities. We analyze the dynamics of asset prices in an economy in which price barriers exist. Our analysis suggests that asset prices and volatility can exhibit jumps when the price barrier is reached. Interestingly, the market's anticipation of future trades can influence prices in the opposite direction from what one might expect. For example, when multiple barriers exist, stock prices can be inflated, rather than depressed, in the proximity of an anticipated stock sale.

Prior research has used inaccurate classification rules to distinguish between stock splits and stock dividends. The CRSP classification of two-for-one stock distributions agrees with the actual accounting treatment only 23% of the time. In addition, the accounting treatment impacts the announcement period reaction—two-for-one distributions accounted for as stock dividends are associated with five-day announcement period returns of 2.70%, significantly greater that the 0.93% announcement returns for distributions accounted for as stock splits. Announcement returns are positively related to earnings growth in the two years following the distribution for stock dividend firms but not for stock split firms. The accounting choice appears to be used to confirm management's private information about future earnings revealed at the time of the distribution announcement.

The properties of variance ratio tests across trading and non-trading periods are examined using the generalized method of moments. For the case of opening and closing return variances, the joint tests indicate that the null hypothesis that the variance of opening returns equals the variance of closing returns cannot be rejected for a sample of New York Stock Exchange stocks. This example demonstrates the importance of accounting for overlapping observations and cross correlation in such frameworks. The conventional average (across assets) variance ratio test is shown to be biased against the null in small samples. Specifically, when non-zero correlations are ignored, previous tests have the wrong asymptotic size. This bias persists in other frameworks as well: although this study confirms earlier findings that the return variance during non-trading periods is significantly lower than during trading periods, test statistics that ignore correlations are shown to be inflated.

This paper assesses the selection and timing abilities of 130 equity mutual funds using a conditional APT model with specified macrofactors, and time-varying risk premia and betas. For all fund categories based on investment objectives, a significant proportion of the funds exhibits negative abnormal asset selection performance based on the unconditional Jensen (1968) alpha, and a reduced proportion of the funds in each category attempts to time the realizations of the macrofactors (including those captured by the residual market factor). The average selection performance of the mutual funds improves and the proportion of funds attempting to time macrofactor realizations declines when measured using the asset selection and factor-timing models with time-varying risk premia and betas.

The National Association of Security Dealers alleges that professional-trader use of the Small Order Execution System (SOES) causes greater security price volatility. We document bidirectional Granger causality between a proxy for professional SOES trading (the frequency of maximum-sized SOES trades) and a measure of stock price volatility. We find that high levels of volatility precede high levels of maximum-sized SOES trades, suggesting that volatility causes more frequent large SOES trades. Likewise, over a one-minute time interval, high levels of maximum-sized SOES trades cause high volatility. Over longer periods, however, intense maximum-sized SOES trading causes lower volatility. Interpreted in conjunction with Harris and Schultz (1997), these results suggest that high levels of maximum-sized SOES trades lead to more efficient price discovery. In light of these results, we believe that efforts to eliminate SOES based on volatility considerations are unwarranted.

This paper develops a corporate bond valuation model that takes into account both early default and interest rate risk. It corrects a defect of recent contributions where pricing equations do not assure that the payment to bondholders upon bankruptcy is no greater than firm value. The bankruptcy-triggering mechanism is directly related to the payoff received by bondholders when early bankruptcy is forced upon the firm. More specifically, the default barrier is defined simply as a fixed quantity discounted at the riskless rate up to the maturity date of the risky corporate bond. As soon as this threshold is crossed, bondholders receive an exogenously specified fraction of the remaining assets. Deviations from the absolute priority rule also are captured. Because it accounts for Gaussian interest rate uncertainty, default risk, and deviations from the absolute priority rule, this model is capable of producing quite diverse shapes for the term structure of yield spreads.