Brown And Warner Event Study 
Journal
of Financial
Economics
14 (1985) 3-31.
USING
North-Holland
DAILY STOCK
RETURNS
The Case of Event Studies*
Stephen J. BROWN
Yale Universiry.
New Haven, CT 06520, USA
Jerold B. WARNER
Universrty of Rochester, Rochester, NY 1462 7, USA
Received November
1983, fmal version received August
1984
This paper examines properties of daily stock returns and how the particular characteristics of these data affect event study methodologies.
Daily data generally present few difficulties for event studies. Standard procedures are typically well-specified even when special daily data characteristics are ignored. However, recognition of autocorrelation in daily excess returns and changes in their variance conditional on an event can sometimes be advantageous.
In addition, tests ignoring cross-sectional dependence can be well-specified and have higher power than tests which account for potential dependence.
1. Introduction
This paper examines properties of daily stock returns and how the particular characteristics of these data affect event study methodologies for assessing the share price impact of firm-specific events. The paper extends earlier work
[Brown and Warner (1980)] in which we investigate event study methodologies used with monthly returns. In our previous work, we conclude that a simple methodology based on the market model is both well-specified and relatively powerful under a wide variety of conditions, and in special cases even simpler methods also perform well. However, the applicability of these conclusions to event studies using daily data is an open question [e.g., Brown and Warner
(1980, p. 21) Masulis (1980, p. 157), Dann (1981, p. 123) DeAngelo and Rice
(1983, p. 348) McNichols and Manegold (1983, p. SS)]. Daily and monthly data differ in potentially important respects. For example, daily stock returns
*This work has benefitted from suggestions of colleagues at a number of seminars, particularly at Rochester,
Yale, and the University
of
of Financial
Economics
14 (1985) 3-31.
USING
North-Holland
DAILY STOCK
RETURNS
The Case of Event Studies*
Stephen J. BROWN
Yale Universiry.
New Haven, CT 06520, USA
Jerold B. WARNER
Universrty of Rochester, Rochester, NY 1462 7, USA
Received November
1983, fmal version received August
1984
This paper examines properties of daily stock returns and how the particular characteristics of these data affect event study methodologies.
Daily data generally present few difficulties for event studies. Standard procedures are typically well-specified even when special daily data characteristics are ignored. However, recognition of autocorrelation in daily excess returns and changes in their variance conditional on an event can sometimes be advantageous.
In addition, tests ignoring cross-sectional dependence can be well-specified and have higher power than tests which account for potential dependence.
1. Introduction
This paper examines properties of daily stock returns and how the particular characteristics of these data affect event study methodologies for assessing the share price impact of firm-specific events. The paper extends earlier work
[Brown and Warner (1980)] in which we investigate event study methodologies used with monthly returns. In our previous work, we conclude that a simple methodology based on the market model is both well-specified and relatively powerful under a wide variety of conditions, and in special cases even simpler methods also perform well. However, the applicability of these conclusions to event studies using daily data is an open question [e.g., Brown and Warner
(1980, p. 21) Masulis (1980, p. 157), Dann (1981, p. 123) DeAngelo and Rice
(1983, p. 348) McNichols and Manegold (1983, p. SS)]. Daily and monthly data differ in potentially important respects. For example, daily stock returns
*This work has benefitted from suggestions of colleagues at a number of seminars, particularly at Rochester,
Yale, and the University
of
References: Ball, R. and P. Brown, 1968, An empirical evaluation of accounting income numbers, Journal of Accounting Beaver, W.H.. 1968, The information content of annual earnings announcements. Beaver, W.H., 1981. Econometric properties of alternative Billingsley, P., 1979, Probability and measure (Wiley, New York). Box, G. and G.M. Jenkins, 1976, Time series analysis: Forecasting and control (Holden-Day, San Brown, S. and J. Warner, 1980, Measuring security price performance, Christie, A., 1983, On information arrival and hypothesis testing in event studies, Working paper, Collins, D.W. and W.T. Dent, 1984, A comparison of alternative testing models used in capital Dann, L., 1981, Common stock repurchases: An analysis of returns to bondholders Dent, W.T. and D.W. Collins, 1981, Econometric testing procedures in market-based Dimson, E., 1979, Risk measurement when shares are subject to infrequent Dodd, P. and J. Warner, 1983, On corporate governance: A study of proxy contests Dyckman, T.. D. Philbrick and J. Stephan, 1984, A comparison of event study methodologies using Fama, E.F., 1976, Foundations of finance (Basic Books, New York). French. K., 1980. Stock returns and the weekend effect, Journal of Financial Economics 8, 59-69. Fowler, D. and C.H. Rorke, 1983, Risk measurement when shares are SubJect to infrequent Holthausen, R., 1981, Evidence on the effect of bond covenants and management Kalay, A. and U. Lowenstein, 1983, Are ‘excess returns’ necessarily economic profits? An analysis of changes in risk and their pricing effects in ‘event time’, Working paper, June (New York