Using XBRL files

More and more companies publish company results not only in quarterly and annual reports but also in the XBRL format. This makes it easier to view the filings and export reporting figures to other prorams like Excel for comparisons and further analysis. Specific features are built into accounting programs to allow for the production of XBRL filings. Some free software programs to view and use these filings have also been made. Two examples that are (mostly) targeted towards US company filings are: is an excellent free web-based program that allows you to view US company filings in XBRL and even allows for an easy comparison for more than one year. The program has an easy export option (after registration) for Microsoft Excel. Calcbench was named the 2012 winner of the XBRL Challenge, a contest for developers to build applications leveraging XBRL-formatted data from the Securities and Exchange Commission’s EDGAR database. A sample screen is shown below:

Dragon View (version 6.1) is a program from Rivet Software. It is a good tool that is easy to use and allows you to export the reported data to Microsoft Excel and HTML formats. The Excel export option is only available in the a licensed version of the program. A sample screen is shown below.


Companies & XBRL

The abbreviation XBRL stands for eXtensible Business Reporting Language. It is based om XML and is being developed as a freely available, open, and global standard for exchanging business information. Two of the earliest adopters are the U.S. Federal Deposit Insurance Corporation (FDIC) and the Committee of European Banking Supervisors (CEBS).
XBRL consists of an XBRL ‘instance’ which contains primarily the business facts being reported, and a collection of taxonomies (called a Discoverable Taxonomy Set (DTS)). These define metadata about these facts, such as what the facts mean and how they relate to one another. The current (2008) version of XBRL is 2.1, with corrections. More background information is available in Wikipedia and a specific XBRL website.

Many large US and internationally operating companies have started posting XBRL files on websites in addition to filing them with the government organizations like the Chamber of Commerce. In 2009 a study was carried out by the North Carolina University and it was found that the XBRL filing contained errors. I do not know how much the XBRL filings have improved the last few years but it is hazardous to take XBRL filings at face value.

The development and use of XBRL to file and report financial statements remains a big step forward, because it makes it easier to use and compare financials statements. This is true not only for investors but also for researchers and students. A study done in 2011 showed that the adoption of XBRL will definitely make it easier to get and evaluate information on company performance and governance.
One of the newest developments is the creation of a Global Reporting Initiative taxonomy (see also an earlier blog post on GRI). This taxonomy will make it easier for companies to also use XBRL for sustainability reporting. The taxonomy is available on the GRI website.


WorldScope coverage update

WorldScope company records now cover annual reports data for (currently) 72014 companies. This includes 46126 active and 25888 inactive companies. This update: 601 companies were added. WorldScope company records are available through Datastream and LexisNexis.

Today I have updated the WorldScope country coverage file and it now includes the latest update as it was posted in the first Thomson Reuters Infostream quarterly publication of 2012.

Major updated Countries (new records):
Australia (35)
Canada (73)
China (73)
Japan (22)
Taiwan (21)
United States (127)


Compustat & stock indexes

One of the latest expansions to the Compustat databases is the inclusion of more stock indexes to the Compustat Global databases. These indexes are available through the part database Index Constituents. This can be found in the menu on the left side in portal Wharton Research Data Services just the same as the with the North America database:



More and more indexes keep being added to Index Constituents database. 4 major European index examples are:

Dutch stock index: AEX
GKEYX: 150262
Ticker: I3NLD014
Start index: 1983
Available range: 1994 – now

French stock index: CAC 40
GVKEYX: 150093
Ticker: I3FRA001
Start index: 1987
Available range: 1987 – now

German stock index: DAX 30
GVKEYX: 150007
Ticker: I3DEU003
Start index: 1987
Avalable range: 1993 – now

UK stock index: FTSE 100
GVKEYX: 150008
Ticker: I3GBR049
Start index: 1984
Available range: 2008 – now

Not every index is available from the start of its original beginning but I assume more historical index component data may be added later.


Referral post to previous blog

My older posts on the earlier blog remain available. Some links to specific sections are:


Stock Volatility and the P/H value

Volatility of stocks and indices has increased in importance the last few years. It is a measure to indicate the risk involved in investing in a stock or stock options. There are several methodes that indicate the volatility for individual stocks. One of these measures is the BETA of a stock. In previous blog posts I have shown how to get the BETA from Datastream using the BETA formula and how to use the formula for several stocks in one go.

Another method to get an indication of the volatility of a stock is the P/H value. The basis of this easy measure for volatility is the difference between the highest and lowest stock price over the last 12 months. The P/H value is calculated by dividing the difference of the highest and lowest price by the sum of these and multiplying this by the standard value 200. The formula looks as follows:

PH = ((PriceHighest – PriceLowest) / (PriceHighest + PriceLowest)) * 200

If the PH value is low then the stock price did not vary very much the last 12 months and has a low volatitlity. If the PH value is high, the stock has a high volatility and it may be riskier to invest in it (or in the stock options).

Here is an example of this I did in Datastream using the functions Max# and MIN# for Unilever and AIR/France KLM for the past year: 7-3-2011 to 7-3-2012. Below you see a screen-capture of the Time Series search I did using the Datastream AFO in Excel:

The formulas (divided by a comma) in Datastream were:


The result of this search for both Unilever and AIR/France KLM is shown in Column C of the following screen-capture:

The P/H value for Unilever is much lower than for AIR/France KLM. This shows that the stock of the latter was much more volatile over the last year. If I compare the rebased price for both stocks over the last year this is also immediately apparent: