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event study basics

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1. 1. The Event Study<br />Hemang C Subramanian<br />Georgia Institute of Technology<br />
2. 2. Definition<br />An Event study is a statistical method to assess the impact of an event on the value of a firm. <br />e.g. Firm Mergers, Hiring a Key Executive, Firing, Layoffs, Plant shutdowns, ERP introductions, IT introduction<br />Event studies are of 2 types<br />Long Term <br />Short Term<br />
3. 3. Why Event Study?<br />The efficient-market hypothesis (EMH) asserts that financial markets are "informationally efficient".(fama 1960) <br />One cannot consistently achieve returns in excess of average market returns on a risk-adjusted basis, given the information available at the time of investment is made.<br />Given this, the effect of an event should be reflected in the security prices of the focal firm.<br />In IS Literature event studies have been used to look at changes in sales for products, changes in firm value, etc. due to a certain phenomenon<br />
4. 4. Example(Xerox)<br />
5. 5. The Method(basics)<br />At firm level – determine the abnormal return for the firm, around the event date.<br />At Industry level – determine the cumulative abnormal returns for all firms in the sample.<br />Obtain statistical significance for the CAR’s across the sample using a Patel Z statistic- Cross sectional analysis<br />Use the Abnormal Returns at the firm level in your model as a dependent/independent variable.<br />
6. 6. The Method( Math )<br />Abnormal Return for firm i, on date t is<br />ARit= Rit-E(Rit/Xt)<br />Rit= return on date t<br />E(Rit/Xt) = Expected Return on date t<br />Xt= Conditioning information (Market Returns, constant)<br />Time t<br />
7. 7. The Method (Math)<br />Period of estimation<br />Window of interest<br />255 days<br />Date t<br />Date t - 40<br />In the Market Model – Rit=ai + bitRmt + eit<br />Retrieve biest and aiestand calculate E(Rit/Xt)<br />ARit= Rit-E(Rit/Xt) = Rit - aiest + bitestRmt<br />Cumulative Abnormal Returns = SArit<br />Z statistic calculated using CAR to determine significance <br />Note: Constant Return Model – Rit=mi + git, There is also a risk adjustment factor used with R’s<br />
8. 8. Disadvantages<br />Over-reaction a possibility <br />Weekend and day of week effects<br />Sampling bias(One day often not the smallest interval)<br />Extraneous factors – inflation, policy decisions, etc. all form the error term (Robustness) – Confounding effects<br />Extrapolation of results to the industry may not find significance<br /> Does this mean Abnormal returns are not valid?<br />
9. 9. History-Literature, etc.<br />1940 – 1960 – John H Myers and Backay (1948), Austin Barker(1956,1957,1958) & Ashley(1962)<br />1968 – 1969 – Ball & Brown, Eugene Fama (studied the effects of stock splits removing simultaneous dividend increases).<br />1970 – 2011 – Mainstream literature in strategy, Finance, IT with wide applications<br />IS Literature<br />IT Investments (Im et al. 2001)<br />ERP System Announcements(Hayes et al. 2001)<br />IT Outsourcing(Oh and Gallivan2004)<br />
10. 10. How to do an Event Study(McWilliams/Seigel)<br />Step 1: Define an event that provides new information to the market.<br />Step 2: Outline a theory that justifies a financial response to this new information.<br />Step 3: Identify a set of firms that experience this event and identify the event dates.<br />Step 4: Choose an appropriate event window and justify its length, if it exceeds two<br />days.<br />Step 5: Eliminate or adjust for firms that experience other relevant events during the<br />event window.<br />Step 6: Compute abnormal returns during the event window and test their significance.<br />Step 7: Report the percentage of negative returns and the binomial Z or Wilcoxon test<br />statistic.<br />Step 8: For small samples, use bootstrap methods and discuss the impact of outliers.<br />Step 9: Outline a theory that explains the cross-sectional variation in abnormal returnsandtest this theory econometrically.<br />
11. 11. Conclusion<br />Event Study methods have significantly evolved to analyse<br /> industry level effects <br /> firm level effects<br />for events such as mergers, acquisitions, introduction of new Technology, failure of technology and a host of news grabbing events.<br />
12. 12. Method(How to?)<br />Define the event of interest.<br />Identify a period of over which security prices of firms involved in this event will be examined, (termed a Window) e.g. (– 1, + 1) OR (– 5 , +5)<br />Obtain the estimators for each stock for a time period with a particular Model, in a timeframe preceding the event.<br />Use the estimated coefficients to calculate the abnormal return to the stock <br />Sum the abnormal return for all days in a Window of interest, to obtain the Cumulative Abnormal Return.<br />
13. 13. Other Models used<br />Fama French Model<br />Rmt – Equally weighted Index, Average Weighted Index, etc….<br />Constant Returns model<br />
14. 14. Null Hypothesis<br />The given event has no effect on the behavior of returns <br />At firm level<br />At industry level<br />