Dear Dr. Müller
Brown and Warner (1985) suggest calculating the t-value as the ratio of the AAR to its estimated standard deviation from the estimation period. Is this appropriate? And don't I have to multiply it by the square root of N as your your significance test formula shows?
Furthermore, they also suggest calculating the test statistic over a interval as the ratio of CAAR to its estimated standard deviation. How can I calculate the standard deviation of the CAAR?
Thank you for your help.
Hi, I have a question about using free event study which is available on the website. the problem is that when I use a credit rating base index as the market price and I have 5 broad categories for the market price in each day.My problem is that I don't know how to list the five market price for each date in the Market data file and how to clarify it clarify my firm dataset and request file? I cannot understand what is the variable group in request dataset.
I already have the file for abnormal return and I just want to use this file to calculate t statistic, is there any simple way for that?
could you please help me to solve this issue?
I try to run your AR calculator with your sample data. It doesn't work: I got an Application error message ???
Dear Mr Müller,
from my point of view using the Patell z test in combination with the mean-adjusted model seems counter-intuitive, since the S(ARi,t,) includes data from a market index (R(m,t)), which are not relevant for the calculation of mean-adjusted AR's. Still your event study engine is calculating it. Would you please elaborate whether you agree with me here, or respectively, why you don't?
Basically, I am using both the mean-adjusted and the market model and I would like to compare the two models' results, which is obviously not possible when using different significance tests. (Due to several adjustments I have made, I am using your engine solely for robustness checks.)
I am looking forward to your reply.
I want to measure long term performance (after 1 year, 3 years and 5 years) of IPO for 400 companies between 2000 to 2010. I want to use BHAR to measure the performance. but I don't know how prepare input data to be used in STATA. I have data in table format in excel as follows:
1. daily market return between 2000 to 2010
2. daily company return between 2000 to 2010
3. IPO listing for each company.
the questions is:
1. how can I prepare my data as you suggested using Comma-separate-value because I have up to 400 companies to go one by one?
2. how can I start my analysis?
I want to analyze abnormal Returns of daily CDS Prices over the past 10 years, especially at certain Events. The CDS are still collected via Bloomberg (different maturities, Senior and Sub CDS, for nearly 100 European Banks). For the estimated return I'd take an iTraxx CDS index.
Would you consider to analyze analogous to your stock return Event study examples? I doubt, that the market model will fit?
Maybe I can upload the dataset for analyzing?
Many thanks in advance,
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.
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?
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?
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"?