Trading Frequency and Event Study Test Specification

We examine the effects of thin trading on the specification of event study tests. Simu-lations of upper and lower tail tests are reported with and without variance increases on the event date across levels of trading volume. The traditional standardized test is mis-specified for thinly traded samples. If return variance is unlikely to increase, then Cor-rado’s rank test provides the best specification and power. With variance increases, the rank test is misspecificed. The Boehmer et al. standardized cross-sectional test is properly specified, but not powerful, for upper-tailed tests. Lower-tailed alternative hy-potheses can best be evaluated using the generalized sign test.

[1]  Kalman J. Cohen,et al.  The Microstructure of Securities Markets , 1986 .

[2]  Donna R. Philbrick,et al.  A Comparison of Event Study Methodologies Using Daily Stock Returns: A Simulation Approach , 1984 .

[3]  Michael D. Atchison.  NON-REPRESENTATIVE TRADING FREQUENCIES AND THE DETECTION OF ABNORMAL PERFORMANCE , 1986 .

[4]  David R. Peterson,et al.  Shelf Registrations and Shareholder Wealth: A Comparison of Shelf and Traditional Equity Offerings , 1986 .

[5]  Arnold R. Cowan,et al.  Nonparametric event study tests , 1992 .

[6]  Ekkehart Boehmer,et al.  Event-study methodology under conditions of event-induced variance , 1991 .

[7]  E. Dimson.  Risk measurement when shares are subject to infrequent trading , 1979 .

[8]  C. Campbell,et al.  Measuring security price performance using daily NASDAQ returns , 1993 .

[9]  Jerold B. Warner,et al.  Using daily stock returns: The case of event studies , 1985 .

[10]  C. Corrado.  A nonparametric test for abnormal security-price performance in event studies , 1989 .

[11]  J. Patell.  CORPORATE FORECASTS OF EARNINGS PER SHARE AND STOCK-PRICE BEHAVIOR - EMPIRICAL TESTS , 1976 .

[12]  Charles J. Corrado,et al.  The Specification and Power of the Sign Test in Event Study Hypothesis Tests Using Daily Stock Returns , 1992, Journal of Financial and Quantitative Analysis.

[13]  Myron S. Scholes,et al.  Estimating betas from nonsynchronous data , 1977 .

[14]  John Rumsey,et al.  Conducting event studies with thinly traded stocks , 1993 .