Event study Deals – Stock Prices – Additional Financials

In this manual we will explain how to get data for the purpose of an event study. While we do describe

the steps in the data collection process, we do not explain how the databases themselves work. For an

explanation on the databases we refer to the manuals available on the EDSC website.

In an event study you want to see whether the market reacts to a particular event, these events could

range from a new law that has passed to M&A transactions. In this manual we use the example of an

event study on M&A deals, because it requires the combination of at least two databases.

To do an event study on M&A deals we need to collect three types of data. First we need to find the

events, in this example these are the M&A deals. Second we need to download the stock prices of the

companies involved in the deals and we need the price of at least one market index. By collecting stock

data of the companies and the price of the market index before and around the deal date we can calculate

cumulative) abnormal returns. Third we may want to do a regression analysis on the cumulative abnormal

returns (CARs) to see which characteristics (of the industry, company, or period) can explain the returns.

To perform this regression analysis we need to collect additional data on for example the companies

involved. Furthermore to perform such an analysis we will need to merge the data from the different

databases.

Step 1 – Collecting your deals Databases: ThomsonOne - Zephyr

The EDSC offers several databases that contain M&A deals. The most widely used databases are

ThomsonOne and Zephyr (manuals). The decision to choose one over the other should be based on your

research question or personal preference. It, however, does not matter for the event study.

To create your deal sample you need to impose some search criteria. For an event study you could think

of the following criteria. First, make sure that the target and/or acquirer is publicly listed. If they are not

publicly listed then you cannot collect stock prices, thus performing an event study is not possible. Second,

the acquired stake might be of interest. In the acquisition of a publicly listed company a commonly used

threshold is a final stake of at least 30% after the deal (but not before), while for private companies this

threshold is set at 50%. To impose such a restriction you will need to think about the allowed

initial/acquired/final stake. For example if you are interested in acquisitions of private companies by

publicly listed companies you could set the following criteria1:

1. Acquired stake is at least 50.01%

2. Initial stake is less than 50%

3. Final stake is at least 50.01%.

Then set the following Boolean search (ignoring other criteria for now):

1 OR (2 AND 3)

The final set of criteria will depend on your research question. Therefore you will need to think about

these criteria carefully and discuss them with your supervisor. For example think about the region,

countries, size of the companies involved, industries (maybe exclude financial), etc.

After you have set all the criteria and you are ready to create your report you will need to add identifiers.

This step is of great importance, because we need the identifiers to find stock data in step 2:

ThomsonOne: If you use ThomsonOne for your deal collection make sure to add the SEDOL code and/or

the Datastream code of the target and acquirer. You can find these by manually searching for them when

“creating your report”.

Zephyr: If you use Zephyr for your deal collection make sure to add the ISIN number and/or the BvD ID

number of the target and acquirer. You can find the ISIN number under Company > Stock Data when

“creating your report”. The BvD ID number can be found under Company > Contact details.

Furthermore in both databases it is important to add the announcement date and the completion date of

the deal as variables.

1 Additionally you could decide to download all deals and add the variables initial -, acquired -, and final stake to your dataset. Then afterwards you can filter your deals using these variables.

Step 2 – Collecting stock prices Databases: Request Table – Eventus – Event Study Tool

In the second step we are going to download the stock prices in order to calculate the CARs. The biggest

difficulty with downloading stock prices for M&A deals is that all deals happen at different dates in time.

Therefore we need to download stock prices for time periods relative to the “event dates”, which is the

announcement date or the completion date depending on your research question. If you are familiar with

programming in statistical software (Matlab, Stata, R, etc.) then you could also download stock prices for

the full period and align the dates and calculate CARs afterwards. However do note that if your period

covers many years and a lot of deals this could become very data intensive. For that reason we advise the

other methods discussed below.

There are several ways to approach the problem of relative dates. The first method is to download the

stock prices “manually” via the Datastream Request Table2. This option will require more work than the

other options, but also offers more flexibility. By using this option you will only get the stock prices for the

specified period. All calculations to get CARs have to be done afterwards. In the output, all dates are nicely

aligned.

The second option is only available for US data and is called Eventus (manual). Eventus provides quite

some flexibility. The tool automatically downloads the stock prices, calculates cumulative abnormal

returns, and offers statistical tests on the outcomes. A drawback however is that the stock prices and

abnormal returns will not be delivered in the output, only the CARs and statistics are delivered.

Finally, the third option is to use the EDSC Event Study Tool (manual). It offers the least flexibility, but is

very easy to use and can be used for both US- and non-US stock prices. Your output will contain the

abnormal returns and by a simply summing these you can get the CARs. For most event studies this

method is sufficient.

Method Database Required effort Flexibility Output

Request Table Datastream Medium High Stock Prices

Eventus CRSP (US Only) Low Medium CAR Statistical Tests

Event Study Tool Datastream Low Low Stock Prices and Abnormal Returns

Bloomberg Excel Add-in using functions3

Bloomberg High High Stock Prices

For all three methods it is necessary to have company identifiers and the announcement or completion

date from step 1. Finally you will need to specify a market index.

2 Note: EDSC does not offer a manual on the request table. Our advice is to follow video tutorials, which can be easily find via Google. Search for “Event Study with Datastream”. 3 If you are familiar with the Bloomberg Excel Add-in than you can choose to create functions, which can download the stock prices for relative periods for the specified companies.

Step 3 – Additional Financials Databases: Datastream (Worldscope) - Compustat – Bloomberg – Orbis

Financials of companies are available in many databases at the EDSC (manuals). However do note that all

databases differ in the available financials. For a discussion see the overview of the most important

differences in the EDSC manual.

You could use the following table to assist you in your decision:

Database Period Coverage Private Companies?

Comments

Compustat North America

1970 - present

US and Canada

No -

Compustat Global

1970 – present

Global (excl. US and Canada)

No -

Datastream ( Worldscope)

1980 - present

Global Yes Works easy with ThomsonOne deal data

Orbis 1990 - present

Global Yes Works well with Zephyr deal data. Strong coverage of small/medium sized private companies. Major drawback: can only download financials for the 10 most recent years.

To download the data from one of the databases you can upload the list of identifiers from step 1 into the

databases. Then choose the financials that you want and start the download. For the specific steps please

see the database specific manuals.

Step 4 – Merging data from databases (example)

After we have collected the financials we will want to merge the deal information with the CARs and the

financials. That way we can run a regression analysis. Hence we have to merge the data from all three

steps. The key to merging data from different databases is the company identifier. However the required

effort will also depend on the software that you will use and your specific research question. For our

purposes we will explain how to merge data with Excel and how to merge data with Stata. Do note that

in some cases you may want to divert from these methods. We will explain the process of merging data

with an example. Please be aware that the following example is only used as an illustration for this manual

and does not represent a real research question:

In this example we are interested in the effect of cash holdings of target companies on the stock prices of

Dutch acquiring companies for deals from 2010 - 2014.4

For this given example we will make use of the following databases5:

Database Reason

Zephyr Deals

Event Study Tool CARs

Orbis Financials

Zephyr – Deals See the figure below for the search strategy in Zephyr. Understand why some criteria have been set and

others have not.

Now to go “View list of deals” to create your custom report. In this report you need to add at least the

following variables:

- Target ISIN number

- Target BvD ID number

- Acquirer ISIN number

- Acquirer BvD ID number

- Announced date

4 Could have used Dutch Stock Exchange… 5 The decision for these databases is specific to this illustration.

I added both the ISIN number and BvD ID number to show in the following steps how one or the other

can be used. The date of announcement is added, because it is necessary for the calculations of the CARs.

Additional variables that might be interesting for your research question should be added as well. For

example (non-exhaustive list):

Variable Reason

Initial - / Acquired - / Final Stake

If you want to use different thresholds you could also download all deals (without the ‘percentage of stake’ criteria) and set the thresholds yourself afterwards. You could then set a threshold of 30% for public targets and 50% for private targets.

Deal Status If you are interested in a subset of completed deals.

Completion date If you are interested in the market reaction around the completion of the deal instead of the announcement

Target - / Acquiror NACE rev.2 code

If you want to control for deals that happened within or cross industry.

Target - / Acquiror country code

If you want to control for deals that happened within or cross country.

Event Study Tool – CARs In the excel file from Zephyr there are two important columns. First the column with the Acquirer ISIN

number. Second the column with the Announced date.

Open the Event Study Tool from the EDSC website. From the Zephyr file copy (Cntrl + c) the Acquirer ISIN

numbers and paste (cntrl + p) these under ‘Company’ in the Event Study Tool.

Notice that in some deals the ISIN code is missing. You could try to find the codes for these companies

elsewhere, but for the purposes of this example I will ignore them.

Now copy the Announced date and past this under ‘Date’. Make sure that Excel recognizes the cells as

dates.6 In this example we will compare everything with the same index. We do however need to find the

appropriate index to compare it with. To find this index you can try to google it or preferable use a

database from the EDSC such as Datastream. In this case I use the MSCI Europe index. For information

about the estimation period and event period see the manual on the Event Study Tool.

Your Excel file should look similar to the figure below. Now if you have access to Datastream you can click

on “Process Table” in the “Request-Table” tab. Otherwise you can send the file to the EDSC and they will

send you the output.

6 Format cells as dates.

Orbis – Financials In our research question we were interested in the effect of target cash holdings on the stock prices of

the acquirers. This means that we will need to download the target cash holdings for the year before the

deal. That way we make sure that the financials are not influenced by the effects of the deal or the new

acquirer.

In most researches you will probably want to download more than only the cash holdings of the target.

For example in your analysis you may want to control for size, profitability, leverage, etc. of the target or

acquirer. For profitability and leverage we then need to define how we calculate them. For example we

can calculate profitability as net income over total assets and leverage as total debt over total assets. All

of these “annual report items” can be downloaded in a similar way as the cash holdings of the target.

In this example we will use Orbis to download the financials because we need the financials of global

targets, which could either be public or private companies. This means that we can choose between

Worldscope and Orbis. In this case I prefer Orbis because the acquirers are Dutch companies, thus there

is a high probability that the targets are concentrated in Europe. Moreover the targets could be quite

small. Orbis has a good coverage of small European firms. Finally because we used Zephyr to download

the financials, the interface of Orbis will be easy to understand.

The first step to obtain the financials is to create a list of identifiers of the targets. In this case we will only

need unique identifiers.7 We will simply do this by copying the list of BvD ID numbers of the targets and

paste them in a new excel file. We prefer the BvD ID number because Orbis is a Bureau van Dijk database

7 Some companies could have been a target more than once in our deal sample. For the purposes of downloading financials we can drop the duplicates and keep only the first time a company has been observed as a target.

and more importantly because the targets could be private companies as well. The BvD ID number has a

better coverage of private companies. Now drop the duplicates8 in the excel file and save it.

The second step is to upload the identifiers into Orbis. After uploading the identifiers into Orbis, go to list

of “view list of results”. Create your report and in this example we will want to include at least the “total

cash” or “total cash and short term investments”. Other interesting variables that I include are the NACE2

code (industry identifier), total assets, total debt, operating revenue, and net income.

Merging the Data Now we have 3 separate files, which we need to combine in order to do our analysis.

In this manual I will explain two ways of matching your data. The first method will use Stata, a statistical

software program. If you know a bit about Stata, this is definitely the easiest way. And even if you do not

know a lot about Stata the simple steps discussed below can be understand with relatively little knowledge

on the program.

The second method will use Excel. Within Excel you can use VLOOKUP to add data or you can use INDEX

+ MATCH. For most users VLOOKUP might be well-known and easy to use, but in large files it is a very

heavy procedure and your file needs to be organized from left-to-right. Meaning that what you are

searching for is always to the left of the array. INDEX + Match is much more convenient and if taken the

time almost just as easy to implement. For that reason I will only discuss INDEX + MATCH.

The key in every matching procedure is having the right identifier (unique or non-unique). For merging

data you will sometimes need a company level identifier or a line identifier. The latter meaning that all

lines in your data must have a unique code. When you want to match files always think about the structure

of the observations (deal level, company level, etc.) in your files. For example, do you have any duplicates

in one of the files? How should I deal with these duplicates? And what is our observation of interest?

In our example we are interested in the effect of the target level cash holdings on CARs of deals. In this

case our number of deals is equal or greater to the number of targets, because one company can be a

target in multiple deals, but each deal will have only one target.9 This also follows from the files in which

the deal file contains more rows (observations) than the file from Orbis. Now our Event Study file contains

the same number of observations (CARs) as the number of observations (deals) in the deal file. Thus we

have:

# deals = # CAR > # targets

8 After you selected the data, go to Data > drop duplicates. 9 In some deals there can be multiple target purchased. In this example I only kept the first target. An easy way out is to act as if each target bought is a separate deal.

Stata

Preparing the files I will first explain how to merge these files in Stata. The key in Stata is that when we combine file 1 and

file 2 then in both of these files the same identifier should be present. Preferable in one of those files the

identifier should be unique for all rows (observations). But before we start matching the files, we will

create Stata files from the Excel files.

Zephyr

Open Stata and then go to: File > Import > Excel spreadsheet (*.xls;* .xlsx). Next click on “Browse” and

import the first Excel File. For the file from Zephyr we need to go to the second worksheet. So under

“Worksheet:” click on the dropdown menu and select “Results …”. Next tick the “Import first row as

variable names”. Then click on “OK”. Now before we save the file we are going to rename the “matching”

variables, which is the identifier. The names of these variables must be exactly the same in each file. There

are several ways to do this.

In the command box, type:

rename TargetBvDIDnumber TARGET_BVDID rename TargetISINnumber TARGET_ISIN rename AcquirorBvDIDnumber ACQ_BVDID rename AcquirorISINnumber ACQ_ISIN

Now we are going to take one extra step. We have our Target company level identifier (BVDID), however

we still need a deal line identifier. And we need to make sure that this identifier is also available in the file

contains CARs. Remember that we used ISIN codes and announcement dates to calculate CARs. Therefore

we are going to create a new variable, which will be the new identifier:

tostring(Announceddate), replace gen Dealidentifier = ACQ_ISIN + Announceddate

The final adjustment is that we already are going to clean the file by dropping observations with

insufficient data. Please do not that these steps are only followed to give an example on how to merge

the dataset. Always understand why you need to drop observations. Therefore:

drop if ACQ_ISIN == "" drop if TARGET_BVDID == ""

Note: The above lines are only useful when you use data from Zephyr.

Save the file.

Orbis

Next up is the Orbis file. Follow the same steps and again make sure that the “Results …” worksheet is

selected. If Stata gives an error when trying to import data then delete the first sheet in Excel in which the

‘search strategy’ is explained.

Again we are going to rename the “matching” variables. Use the following line:

rename BvDIDnumber TARGET_BVDID

Save the file.

Event Study Tool

Last up is the file containing the CARs. I prepared the file in Excel, by adding the abnormal returns to get

CARs. Also I reshaped the data within the file. See the figure below:

Now follow similar steps as for the previous files. Upload the file in Stata and rename the variables:

rename Name ACQ_ISIN tostring(EventDate), replace gen Dealidentifier = ACQ_ISIN + EventDate10

Save the file.

Merging the files Finally we are ready to merge the data. First I will match the deal data with the CARs. Then I will add the

financials to these deals. Again you could use codes to merge the datasets, but I will explain the point-

and-click method.

Open the file from Zephyr. Now go to Data > Combine Datasets > Merge two datasets. A pop-up will

appear. In this screen select ‘One-to-one on key variables’. In the dropdown under ‘Key Variables: (match

variables)” choose Dealidentifier. Finally in the last line, click on ‘browse’ and search for the CAR File.

After the files have been matched drop the ‘_merge’ variable or rename it.

Now to add the file from Orbis we are going to follow similar steps. Except in this case we will select

‘Many-to-one on key variables …’ and as ‘Key variable’ we are going to select TARGET_BVDID. We choose

many-to-one because we have multiple deals that need to be merged to the same target company.

Choose the Orbis file and click on ‘OK’.

10 Notice that the dates are in MM/DD/YYYY. For that reason we also changed our Zephyr Stata file into that format.

Potential issues:

- Sometimes you have duplicates in your master or using file. Open the file and check for duplicates

via Data > Data Utilities > Tag duplicated observations. As variable set your “matching” variable,

which you thought to be unique. Then as ‘New variable name’ you can enter for example dup.

Click on ‘OK’. Now go to the data editor and check why you have duplicates. If it is not important

then you can decide to drop the duplicates from the sample.

- The results will show the number of matches. Check if everything went well. Sometimes we had

to drop deals with insufficient data. Other deals might not have had enough stock price data to

calculate abnormal returns.

EXCEL: INDEX MATCH Although it is not necessary it might be easier to put all files into a single excel sheet (on separate tabs).

First of all we are going to create unique lines for the CARs and Zephyr. For Orbis this is not necessary. We

do this by simple combining two columns. For the cumulative abnormal returns:

For Zephyr we are going to combine the Acquiror ISIN number and Announced date:

Now if we start from the Zephyr tab and add the other two, then do the following:

Use the INDEX function to find the CAR that corresponds to the row in Zephyr. Within this INDEX function

use the MATCH function to find out which row in the Zephyr tab corresponds to which row of the CAR

tab:

Now to add the data from Orbis to the Zephyr tab we are going to use the same two function. However

instead of using our “Unique line” column we can use the “Target BvD ID number”:

This formula can be dragged across the entire file.