Perform an event study with the data given for the 6 dividend omission events (the data is given in the file "dividend omission permno.prn"). The Microsoft Excel text file contains both the permnos and the event dates. Eventus requires that you upload this file in step 1 of Eventus. Once you have performed the event study, report the following information:

What are the estimates from the market model for alpha and beta for each of the 6 securities/events?

Identify date and mean abnormal return (derived from the market model) for all dates where there is evidence to reject the null hypothesis that the mean abnormal return equals zero. State the level of statistical significance, 10% level, 5% level, or 1% level.

Hint: Note that you will report the strongest statement you can correctly make about statistical significance. For example, if the p-value is .03, then report "statistically significant at the 5% level."

Eventus will permit you to select more than one event window. Examine event windows of different duration. For example, examine event windows beginning as early as day -10 and ending as late as day +10. Also, examine windows beginning prior to the event date and ending on the event date (day 0) as well as event windows beginning with the event date and ending after the event date. Examples include event windows (-10, +10), (-5,0), (0,+5), (-1,0), (0,+1), (-1,+1), and (-2, +2). Identify the event window and the mean cumulative abnormal return derived from the market model for all event windows where there is evidence to reject the null hypothesis that the mean CAR equals zero. State the level of statistical significance.

If the mean CAR is negative, how do market participants view dividend omissions?

For all of your tests for statistical significance, use the Portfolio Time Series (CDA) test statistic which employs the test (t-test) with which you are familiar.

Part II

You will now re-run the same event study. However, first make the following modifications in Eventus to the event study performed:

Under Step 4: Alternate Windows, select only the alternate window of “begin” -1 and “end” 0. This means that Eventus will calculate mean CARs for only the two day event window of days -1 and 0.

Under Step 5: Output Parameters, also select DETAIL=FULL. This will now provide you with both ARs and two day CARs for each observation. In your output, you will have one two day CAR corresponding to each of the six observations. You will then use the output for the six observations to create a variable “2 day CAR.”

First, complete the MS Excel Spreadsheet, "Data for Problem Set 4 Cross-Sectional Regression." You will complete the column with missing data. The missing data are the 2 Day CARs from the Event Study. Make sure that each CAR in your spreadsheet appropriately corresponds to the firm name/event date. In other words, getting the order correct is important.

Once you complete the data, run a regression where “2 Day CAR” is the dependent (Y) variable and the 3 dummy variables provided are the independent (X) variables.

Report the following:

Provide a print out of your data and regression output.

What are the coefficients estimated in your regression? Report the sign (positive or negative) of each coefficient. Provide a short plausible explanation, based on your knowledge of finance, for why each estimated coefficient sign is positive or negative.

Report if there is any statistically significant evidence that you can reject any of the null hypotheses that a coefficient equals zero. Report the level (1%, 5% or 10%) of statistical significance.

Subject | Business |

Due By (Pacific Time) | 07/23/2015 12:00 am |

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