**What is exactly M?**

Dear Mr. Müller,

Regarding the parametric T-test for one sample Event: Could you explain me the size M (matched returns), please?

My event window is +/- seven days surrounding the announcement day of an acquisition. So L2 is 15 in my analysis, right? Is M also 15?

Thank you in advance!

You can also answer me in german.

Best wishes,

Tim Rothermel

**Grouping Variable**

I am trying to run an even study test by event study tool. I found a column called grouping variable in the "request file", and in the sample file it is given as "addition". I am not quite sure what grouping variable is and what "addition" indicates. Could you kindly instruct me?

**Competitor Portfolio**

I am examining an individual event. According to your recommendations a parametric t-test (Nr. 1 on the website) is applicable. Besides the effects this event has on the stock returns of the company responsible for the event, I'd also like to examine the effects on the firm's competitors. Treating individual competitor stocks as independet is almost surely inappropriate, since I would expect a fair amount of correlation among competitor retruns. To adjust for this possibility, I create a portfolio composed of all relevant competitors and calculated the abnormal returns of this portfolio.

1.) Can I apply the same test statistic to test for significant AR of the competitor portfolio as I do for the individual focal firm?

2.) Is there a way to avoid portfolio creation that still yields statistically meaningfull/ unbiased results? Which test would be applicable in that case?

**Single-Day Event Study**

I am currently working on a single-day event study. I came across the paper by Kolari and Pynnönen (2010), which proposes two test statistics that can handle cross-sectional correlation: ADJ-BMP and ADJ-PATELL. Is there a way to correct for cross-sectional correlation using the "Event Study Engine"?

**Standard Deviation and Variance of CAR**

When looking to your excellent summary of event study statistics , I've something that I am not quite sure is correct. When you present the formulas for the Standard deviation of the CAR in the BMP test, I think you mean that the equation in question is for the variance of CAR and not the Standard Deviation, meaning that a square is missing in the Market Model, Comparison Period Mean Adjusted Model and the Market Adjusted Model left side of the equation. Maybe I am missing something but I want to be sure.

**Difference in mean - pre/post financial regulation**

If you are conducting a study where you test AAR/CAAR in association with corporate credit rating changes before and after a financial regulation (ie. test if the effect on the stock market from a credit rating change (Moody's) is more/less extreme after the regulation), how would you test for the difference in mean?

I have looked at multivariate regression models but i don't quite understand it. Could you be so kind to elaborate on how you would test for the difference in post/pre AAR/CAAR.

**Possible Error in R Code**

Just a short note: I guess there is a sort of small typo within the R code example provided within the 'local tools for event studies'-section. When calculating the simple returns, the variable filled should not be called firmSub$firmSub but rather firmSub$firmReturn.Otherwise it will not be found within the OLS estimation and further on.

Besides: I would appreciate more extensive event study R code examples a lot, but of course see your need to focus on other priorities :D

**Adjusted significance tests**

I'm having problems in calculating both the adjusted Patell test and the Adjusted BMP test. Could you explain me how to get the average of the sample cross-correlation of the estimation period abnormal returns? Is this the Pearson correlation coefficient or anything else? In the analysis report you provide it is reported the first-order autocorrelation, is this in any way utilised? I'm stuck on this step and your help would be really useful.

**Cross-Sectional Test**

Ich wüsste gerne woher bei der Erklärung des Cross-Sectional-Tests die Wurzel N vor dem Bruch kommt. Die leitet sich für mich nirgends heraus ab und ist auch unterschiedlich zu allen gängigen Artikeln über ein und dieselbe Signifikanztest-Art.

**bARC Error: Empty Estimation Window was Extracted**

My data has missing values of stock price for some dates in estimation window of some events, therefore bARC result give an error for those events "Empty estimation window were extracted". As I don't have stock price data of firms for those missing dates, is there any way to perform analysis successfully for those events.