Methodology of an Event Study
In this section we outline the methodology of an event study. In suc- ceeding sections we apply the methodology to a number of different cases. An event study is composed of three time frames: the estimation window (sometimes referred to as the control period), the event window, and the postevent window. The following chart illustrates these time frames:
The time line illustrates the timing sequence of an event. The length of the estimation window (also referred to as the control period) is rep- resented as T_{0} to T_{1}. The event occurs at time 0, and the event window is represented as T_{1} + 1 to T_{2}. The length of the postevent window is represented as T_{2 }+ 1 to T_{3}. An event is defined as a point in time when a company makes an announcement or when a significant market event occurs. For example, if we are studying the impact of mergers and acquisitions on the stock market, the announcement date is normally the point of interest. If we are examining how the market reacts to earnings restatements, the event window begins on the date when a company announces its restatements. A common practice is to expand the event date to two trading days, the event date and the following trading day. This is done to capture the market movement if the event was announced immediately before the market closed or after market closing. The event window often starts a few trading days before the actual event day. The length of the event window is centered on the announcement and is normally three, five, or ten days. This procedure enables us to investigate prevent leakage of information. The postevent window is most often used to investigate the performance of a company following announcements such as a major acquisition or an IPO.
The estimation window is also used to determine the normal behaviour of a stock's return with respect to a market or industry index. The estimation of the stock's return in the estimation window requires us to define a model of "normal" behaviour: Most often we use a regression model for this purpose. 3 The usual length of the estimation window is 252 trading days (or one calendar year), but you may not always have this many days in your sample. If not, you need to determine whether the number of observations you do have is sufficient to produce robust results. As a guideline, you should have a minimum of 126 observations; if you have less than 126 observations in the estimation window, it is possible that the para meters of the market model will not indicate the true stock price movements, and thus the relationship between the stock returns and the market returns. The estimation window that you select is supposedly a period that was free of any problems-that is, a period that reflects the stock's normal price movements. The postevent window allows us to measure the longer term impact of the event. The postevent window can be as short as one month and as long as several years depending on the event.