If this article were written in 2001, its advice would center on how to effectively pull data out of an annual or quarterly report and make best use of it.

Key tips: Read from the back, forward. Read footnotes first.

Now, that doesn't matter. Not in the same fashion, anyway.

With the advent of a tagging system for the numbers and text found in financial reports, there essentially is no need to pull anything out of an income statement or balance sheet. That's done, in advance.

Now, if you're a fund manager, the challenge instead is to use the quickly accessible data put at your fingertips by the eXtensible Business Reporting Language of the Web. Start from the risk-return summaries that your firm must file about the funds you create and manage. Then, consider all the reports filed about the companies in which your funds have invested as part of a huge relational database that will let you compare and contrast the performance of every piece of your holdings.

This "drill-down effect" of XBRL will allow those managers who use it to analyze fund assets "to spot issues first," said Robert J. Farrell, the newly installed chief executive of EDGAR Online, a developer of financial reporting services that hinge on the interactive nature of this language.

Managers will be able to more quickly and competently analyze which securities they hold contribute to their funds' performances the most, which have value that might have been hidden in the old paper and spreadsheet transfer days and get constant updates on key parameters fed automatically into the analytical models they build, using familiar function calls of spreadsheets and pull-down menus.

Risk-return summaries typically include fees, charges and expenses of a given fund, as well as annual returns for the last five years. Mutual funds this year are required to provide the risk-return sections of their prospectuses on their Web sites in XBRL format. This follows previous requirement by the Securities and Exchange Commission that public companies file their quarterly and annual reports in the same format.


No More Extraction


Which now makes it possible for service providers like EDGAR Online to load all the data from all the reports into a single huge database, then use tags and formulas to define the relationships between information in all the reports and then let users move back and forth between reports as if they are indistinguishable. And, as desired, direct the data to be put into spreadsheets of their own making, at will.

"Low-level data extraction is giving way to high-level data analysis," said Elias-John Kies, director of analytics for the product group at EDGAR Online, which is based in Rockville, Md.

This means, for instance, that a manager wanting to analyze the performance of a rival fund that invests primarily in Nasdaq 100 stocks can start with the average annual return of the fund, since its inception, then look at the holdings in the portfolio and start to compare the performance of individual stocks on pertinent parameters.

That means clicking on, say, digital device maker Apple Inc. and semiconductor supplies provider Applied Materials Inc., and comparing their performance in managing their international expansion.

From their respective annual reports, a user can fairly quickly see how they compare on the percentage of revenue coming from international operations, using the tools provided in EDGAR Online's iMetrix service that runs on top of the database it maintains of all available XBRL reports.

Apple draws 56% of its revenue from markets other than the United States. Pretty good. But Applied Materials is at 86%, which would seem to indicate that it's much more adept at expanding and operating abroad.

But what really matters is what you take to the bottom line. Which might lead a fund manager to want to look at the data produced by drilling into the tag for "EffectiveIncomeTaxRateContinuingOperations" and some related fields.

The effective income tax rate for continuing operations for Apple? Twenty-four percent. For Applied Materials? Thirty-two percent. Fifty percent higher.

The manager still has to figure out what Apple is doing that keeps its tax rate down, in such dramatic fashion. But either Apple is doing a great job of managing foreign taxes on its operations or Applied Materials is a laggard. Or both. And, given that Applied Materials does 86% of its business abroad, the manager probably wants to call Applied Materials first, to get a line on what's going on. Or is not going on.


XBRL 'Factor'


Similarly, a manager might want to figure out if there are risks in holding shares in firms with unfunded pension liabilities. In this case, the manager uses fields that are tagged in ways that define the assumptions used in calculating long-term returns on pension assets.

In the case of chipmaker Analog Devices Inc., the iMetrix tool automatically throws up on screen the expected long-term return on its pension assets as 7.0%. In an era when-for nearly three years-inflation has been running at under 3.0%, this may be prima facie evidence of over-optimism. And underfunding of a pension plan. Time to place a call. Particularly if, by a quick click to another piece of data, further inquiry indicates that 74.7% of Analog Devices' holdings are in illiquid unit trust funds.

This kind of ready comparison between funds and between individual holdings hopefully will create what Kies of EDGAR Online calls an "XBRL Factor," or effect.

Firms that find they need to look good compared to their peers will, he believes, start to provide more information about themselves.

Companies "won't want to wiggle around and not be as transparent as possible," Kies said.

If, for instance, you're operating an airline, and you're the only one that does not break out fuel costs every quarter, you're going to fall in line pretty quickly. Or face the obvious assumption that there is something to hide.

The effect could end up producing more information, over time, in line of business and geographical reporting, for instance, he believes.

Which in turn will make it easier for a portfolio manager to figure out why the returns in his firm's emerging markets fund is not keeping up with the returns in a rival fund.

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