Calcbench API

The Wall Street Journal Uses Calcbench, why not you too?

Friday’s (8/1) edition of the Wall Street Journal carried an article entitled Record Cash, Record Debt   by Ted Mann and Theo Francis.  The authors worked with Calcbench in order to obtain data for their article.  Included in the dataset were Unremitted Foreign Earnings and Debt levels across the entire US filing universe. 

The objective of the authors was to identify firms with increasing overseas earnings and increasing debt levels.  The results are fairly straightforward, defer taxes on overseas earnings, borrow cheaply against the overseas earnings, invest where you can make more, and as an added kicker, take a deduction on the interest paid on the debt.  It looks like a corporate win-win.  Francis and Mann found more than 200 US firms used this technique effectively in 2013 (Francis, Mann, WSJ).

Firms and investors have been executing carry trades like this forever, but using tagged financials will help identify patterns more quickly.  This in turn moves away from anecdotal evidence into the realm of hard fact.  Anyone with the remotest of interest in economics or finance should be running to get at this information. 

Why did the authors at one of the most prestigious newspapers in the world come to Calcbench?  They couldn’t get the data anywhere else. 

The takeaway for users is that just like our friends at the WSJ used Calcbench, so can you.  Sign up today!

Chart of the Day- Increasing Inventory Among Retail Stores

We were curious to see whether or not there would be an increase in inventory among retail stores over the past three years. We chose to look at two sectors General Merchandise (SIC 5300) and Apparel and Accessory Stores (SIC 5600). These sectors include companies like Walmart, Target, GAP, and American Eagle. In both sectors, inventory grew fairly steadily since 2011. We chose to use the sector averages for the inventory accounts in each year since the vast majority of companies followed the same trend.


There are a few possible explanations for the growth in inventory. One explanation could be that “brick and mortar” stores recognize that their competitive edge is that their customers do not have to wait to buy products from their stores. The added convenience of purchasing and returning goods is enough to justify whatever price difference may exist in a price sensitive industry between them and online stores. The “brick and mortar” stores’ competitive edge is lost if they do not retain enough inventory in their stores and warehouses to keep the shelves and racks stocked with any item the consumer may desire. This is merely a possible explanation as there could be many other causes influencing this observed trend.

To see for yourself in more detail, head to the Benchmark tool, look at SIC Codes 5300 and 5600, and select Inventory as a data point.

XBRL Calculation Relationships, What Are They?

Today we heard that the SEC is sending, or at least planning to send, letters to companies complaining about missing calculation relationships in their XBRL filings. Of course this is good news…these relationships provide very valuable information for data users to understand what is going on with the numbers. 

But many people may not know what a calculation relationship is, and why it’s so important. So here is a visual representation from Calcbench’s website. These are the calculation relationships for a cash flow statement from a recent 10-K.

As you can see, it simply shows how all of the elements add up. The total change in cash for the period is calculated by adding up four elements, which in turn are calculated by adding and subtracting various elements of their own.

Calcbench on a Mission: Understanding & Enhancing XBRL Data Quality

We all know that bad data in means bad data out.  For that reason, since our founding, Calcbench has had an unwavering commitment to enhancing the quality of XBRL data, so much so that we’ve built it into both our platform and our processes. This way we ensure that we don’t pass any XBRL data quality problems on to our users.

As part of this dedication to data quality, we recently set out to quantify all of the errors we’ve identified and corrected in XBRL filings filed with the US Securities and Exchange Commission (SEC) over the past several years. Through this study, we examined several types of mistakes most likely to throw off an end users’ analysis, including errors in the Document and Entity Information (DEI), scale errors, and sign switches. (Please note, these are NOT the only types of errors a filer can make!)  What we found was somewhat encouraging: over time, companies seem to be getting better at catching common errors before they file. Yet, clearly a lot more can be done.  And we remain committed to providing as much feedback as possible back to corporate reporting professionals about their own filings, so they can learn from past filing errors (something we do via our complimentary Filer Portal service).

We know that XBRL data holds significant benefits, including easy access to significant amounts of valuable data.  However, our findings suggest that most XBRL filings contain errors, most of which are relatively easy to correct and may be the result of a learning curve by both filers and third parties creating the XBRL filings. Nevertheless, the prevalence of errors suggests that filers should pay more attention to their filings as these errors can expose filers to further actions from the SEC and to potential litigation from financial statement users.

You can read a more comprehensive overview of our findings in our recent report. Some of the key insights include:

  • The most frequent errors are sign switches (about 50% of filings), followed by scale errors (about 8% to 12% of filings) and DEI errors (about 3% of filings).
  • Approximately 3% of all filings have DEI errors. These errors seem to be consistent over time, and we only observe a slight decrease in recent filings.
  • The rate of scale errors is significant (up to 12% of filings in Q4 of 2012) but it is decreasing. It seems that scale errors are made by both small and large filers and appear in both the face financials and the notes to the financials.
  • Most scale errors occur in tags associated with shares. However, a significant number of scale errors are made in tags like Revenues, Net Income, and Total Assets, which are frequently consumed by users of financial data. Scale errors are relatively easy to detect and correct.
  • Sign switches do not seem to have decreased over time. About half of all filings have at least one sign switch. Sign switches seem to have been more prominent with larger filers earlier, but the smaller filers are the ones more likely to have them in later years.

To learn more about the current state of XBRL and read more of our findings, we encourage you to read our report, “What Filers Should Know about the Quality of XBRL Filings”.

Calcbench’s ‘Letter Writing’ Campaign for Data Quality

At Calcbench, over the past two years, we’ve flagged and corrected, automatically and by hand, hundreds of thousands of errors or inconstancies in XBRL filings…it’s what we do to ensure we have the highest quality database possible for our users. 

However, recently we’ve been more active in sharing this information back with the people creating the filings. Last fall we launched our Filer Portal, a complimentary service that XBRL filers can use to check the quality of their filings from our perspective, as well as study their revisions histories, and see how their information looks to an outsider. Unlike other consistency checks, our Filer Portal is the only tool we are aware of that examines all of the information for that company in aggregate in order to find problems such as errors of scales, sign switches, and date errors. Over the next year we’ll keep adding to the Filer Portal to give filers the best info we can about their quality.

But we didn’t stop there. Since the beginning of 2014, Calcbench has been sending letters detailing problems we’ve detected back to the company. Below are some snapshots from two such letters. For our full report on the current state of XBRL data quality, click here.




Analyzing XBRL Tag Variations in Inventory

As part of the XBRL tagging process, companies assign XBRL tags to specific line items in the financial statements. The XBRL taxonomy published by FASB offers companies choices in how to tag information. There are many standard tags for a company to apply that could be associated with one common line item. Inventory, for example, could be tagged as <InventoryNet>, <InventoryGross>, <RetailRelatedInventoryMerchandise>, and so on depending on the specific nature of the line item. When there are no tags that define the line item sufficiently, an extension tag is created by the filing company. This is reserved for cases in which the line item is truly unique, and requires a more descriptive XBRL tag. Having more descriptive tags are excellent for stakeholders because they offer a better perspective of the company’s financial statements, but it makes benchmarking much more complicated.

Calcbench accounts for variations among different tags associated with their respective line items, and narrows them down to their basic theme so that the numbers associated with the tags are reported with the correct line items in the financial statements. If Calcbench accounts for variations among the different tags, then the differences among the tags might seem unimportant and undeserving of attention to a user. However, companies assign different tags for a reason, and the decisions are not necessarily made arbitrarily and may actually convey some information.

XBRL tags can essentially function as predefined indicators. Financial investors can use the Benchmarking Tool in Calcbench to discover tag variations. After quickly locating and reading the taxonomy, a financial investor will have a deeper understanding of the differences between business operations among competing companies. XBRL is another powerful tool that benefits everyone, and the benefits transcend beyond the ability to rapidly distribute interactive financial data and display it similar to what is possible via Hyper Text Markup Language (HTML).

The following is an example of an analysis of the tags companies use to tag their inventory. The example uses Calcbench’s Benchmarking and Analysis tool and the As Reported Companies in Detail tool.

Click here to read the full report.

Q1 2014 Wrap Up - Revenue Growth On Track

With most companies filings their Q1 2014 financials we wanted to offer an overview of how do the financial results compare to last year (Q1 2013). Overall, it seems like Q1 2014 compares relatively favorably to Q1 2013, showing a significant increase in Revenue but a decrease in Net Income for larger companies. It seems like the smallest companies had the best financial results and are investing heavily in their future.

We examine the Year over Year change in average measures per firm. This analysis excludes financial firms.

Overall, it seems like average Revenue has increased for all size companies. At the same time, for the larger companies, the Cost of Revenue, has increased by more than the Revenue resulting in a decrease in average Net Income. The smallest companies showed a very moderate increase in the Cost of Revenue, resulting in a large increase in Net Income. **Please note that Net Income includes onetime charges.

As a next step we examine what happened to the companies’ resources and potential impact on their future. We observe an increase in average cash held by the companies with the smallest companies increasing their cash holdings the most. The increase in Total Assets and Capital Expenditures seems to indicate that companies are increasing in size and spending more on Capital Expenditures. The smallest companies may see the brightest future.


Overall, Q1 2014 was mixed. We observe an increase in Revenue, but an increase in expenses resulting in a decrease in Net Income for the larger companies. It seems like the smallest group of companies fared the best, showing a substantial increase in Net Income, Cash and Capital Expenditures.

T-Mobile’s “Uncarrier” Business Strategy

Guest blog post by Zach Burnham, Accounting Student, Suffolk University.

By now, most people are probably aware of T-Mobile’s new aggressive business strategy. The self-proclaimed “Uncarrier” has been antagonizing AT&T and Verizon, the two dominant corporations in the cellular carrier industry. After the merger between T-Mobile and AT&T did not succeed, T-Mobile was forced to expand on its own. They reached a deal to acquire MetroPCS by late 2013. With a new marketing campaign and additional assets, T-Mobile is trying to threaten the industry’s status quo.  After reviewing T-Mobile’s financial statements, it seems that consumers are enjoying the unconventional business strategy.  Using Calcbench’s benchmarking tool, I was able to quickly compile data into a series of useful tables.

The Revenue Growth graph shows that T-Mobile’s revenue grew, in 2013, by a little more than $2.2 billion, which represents a 46% increase. This increase is significantly higher than the increase in revenue of AT&T and Verizon (about 5.5%).

T-Mobile also reported net income of $35 million for 2013, which is substantially better than the $7.3 billion loss in 2012. The substantial losses in 2012 and 2011 were likely due to impairment charges (impairment charges are an operating expense that allows a company to write off worthless goodwill). It is interesting note that the sudden increase in Net Income for AT&T and Verizon is simply explained by a decrease in selling, general and administrative expenses in the 4th quarter.


In addition to making the company more profitable, T-Mobile is addressing the lack of wireless coverage in less populous areas. It is certainly an obstacle preventing potential customers from switching to T-Mobile, and therefore, a hindrance to capturing a respectable market share. Throughout 2013, the property, plant, and equipment account has increased by over $11 billion, and the spectrum licenses account has increased by $16 billion (spectrum licenses are licenses granted by the FCC that allow a broadcaster to use a certain band wave). The increases in these accounts indicate that T-Mobile is pushing to expand wireless coverage drastically.  AT&T and Verizon have not had remotely comparable investments in the past 2 years.

The substantial increase in T-Mobile’s Total Assets of about $16 billion from 2012 to 2013 (which represent almost a 50% increase in assets), seems to have been financed roughly equally by debt and equity.  Both debt and total equity increased by over $8 billion each.

AT&T and Verizon have been responding to T-Mobile’s business strategy by instituting plans that are similar to the generous options offered by T-Mobile. It seems they have real concerns that T-Mobile can steal market share.

To delve deeper into T-Mobile’s, and other companies’, financial statements, sign up for a free Calcbench trial. Also, make sure to check out the Knowledge Base and Resource Library (located under the “Resources” tab) for more information on how to begin using the powerful analytical tools Calcbench offers. If you have any questions, please send your emails to

What Kind of Firms Hold Level 3 Instruments and Recognize Mark-to-Market Adjustments in Earnings?

Guest blog post by Robson Glasscock, CPA and Ph.D Candidate. Robson uses Calcbench data in his
project and is sharing some of his findings here.

One of the benefits of using XBRL data from Calcbench is the ability quickly obtain data that would otherwise only be available via manual searches of EDGAR filings.  As accounting rules and disclosures evolve other database services may eventually be updated to include the new information, but real-time access to machine-readable data from fillings is advantageous for a variety of reasons. 

The current example is related to firms that hold Level 3 instruments per Accounting Standards Codification (ASC) 820, and recognize valuation changes in instruments still held at the balance sheet date (i.e., mark-to-market adjustments) in earnings.  ASC 820 defines Level 3 assets and liabilities as being valued using “unobservable” inputs.  The standard goes on to say that unobservable inputs, “… reflect the assumptions market participants would use when pricing the asset or liability.”  This post explores whether these assets and liabilities are typically held by financial services firms and, if not, which non-financial services industries tend to hold more Level 3 instruments.

Between January 1, 2009 and July 1, 2013, XBRL data is available for approximately 186 firms that report unrealized gains/losses on Level 3 instruments in earnings. Of these, 103 firms are financial services firms and 83 firms are non-financial services.  Contrary to what many people might think, including many academics I have spoken to, Level 3 holdings do not appear to be dominated by financial services entities.  Within the non-financial services firms, the two-digit SIC codes with the largest representation are 49 and 13, respectively.  Industry specifics are reported below: