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 In Parts One and Two of this article series, I examined how reported fund expenses and less readily measurable expenses like transaction costs reduce fund returns. I suggested using the definition of index tracking error commonly used by ETF analysts and advisers to organize the analysis of the elements that determine how well or how poorly a fund performs. In this third and final article, I describe XBRL, the key to the availability of accurate fund data and to the development of improved fund evaluation software that investors and advisers will use to improve fund selection. I also address some specialized tools that are useful in examining and evaluating important fund features.
Extensible Business Reporting Language: The New Data Standard For Corporate And Fund Reporting
So far, fund industry use of XBRL consists of a few over-publicized SEC filings of risk/return summary information from a small number of mutual fund prospectuses. The published information includes a few details of the funds’ investment objectives, costs and historical performance. The applicability of XBRL to a full range of financial data is illustrated by the fact that it is now mandatory for many corporate filings with the SEC. With required use of XBRL, the accuracy of available corporate financial data has improved dramatically. The Investment Company Institute (ICI) has created XBRL categories and templates for mutual fund filings.1 When this project is fully operational, funds will report to the SEC using the XBRL format, and fund analysts and advisers will be able to use XBRL to assemble data for a full range of fund analyses and comparisons.
The significance of full XBRL fund reporting is that analysts will be able to access specified elements of data, analyze data from an individual fund or do comparative analyses of competitive funds. Most of the analyses illustrated in Part Two will be performed using spreadsheets and macros or formal programs for periodic reports and comparisons. The key underlying change will be standardization and tagging of fund data elements so that the data everyone uses will be the data the fund files with the SEC.
To understand the potential significance of comprehensive XBRL data, one need only read the descriptions of gathering, “cleaning” and screening mutual fund data in the academic studies of funds that have been undertaken over the past 20 years. Mutual fund data extraction has moved from handwritten ledgers to manual copying of poorly formatted hard copy SEC filings to special-purpose text search methods that extract data from eclectic electronic reports filed with the SEC. Today changing formats, missing data items and confusing aggregations of fund family data that differ in format from one period to the next make data collection the hardest part of any comparative analysis of funds. Different fund services often publish different numbers for the same fund. The adoption and widespread use of XBRL for fund data will not eliminate fund data problems overnight, but it promises to revolutionize most fund comparisons. The best description of the advantages XBRL brings to fund data analysis that I have seen is in a speech former SEC Chairman Cox gave to a group of financial analysts in late 2008.2 In his speech, Chairman Cox actually applied the “don’t try this at home” admonition (which he attributed to reports describing one of Harry Houdini’s feats) to the difficulty of extracting useful fund data from SEC reports without XBRL. On my Scouts’ honor, the Mr. Wizard story in Part Two of this article and the rest of this discussion of XBRL was part of a draft before the former Chairman made his speech.
XBRL is an open standard. It carries no royalty or licensing fees. The availability of clean data in a standard format from most funds will permit an adviser or even a committed individual investor to analyze funds with more reliable data than the best fund services have today. In addition to data assembly and analytical macros provided by financial Web sites, a wide range of analysts and market pundits will be able to produce custom analyses at low cost. Questions that are rarely asked because the data to answer them has been inaccessible will be asked and answered with ease. Everyone who cares will have free access to a better fund database than any fund service could assemble today. The fund rating organizations will be competing with developers of new fund analysis and evaluation software. Investors and their advisers will be the beneficiaries of this competition.
The downside to the XBRL story is that a full XBRL reporting standard is not yet mandatory for funds. Some funds may decide not to use XBRL for all data, including important non-financial data. It is impossible to predict the pace at which the XBRL standard will be rolled out and the data from it roll in. If most of the major fund companies submit a full range of XBRL data, the pressure on other funds to conform will be powerful. Realistically, however, a critical mass of funds is unlikely to submit full data without a mandatory standard.
The “financial crisis” of 2008 diverted attention from the SEC’s normal operations and, unfortunately, diverted attention from XBRL, of which former Chairman Cox was a major advocate. Chairman Schapiro is as fully attuned to the regulatory needs of fund investors as anyone, but she and her colleagues at the SEC have far too many issues that need their attention. Fortunately, the case for XBRL fund data is compelling. The advantages of XBRL data from funds are so great that the XBRL rollout will provide data necessary to reduce other elements of the commission’s workload.
There Is A Wide Range Of Quality In Fund Touts, Tools And Techniques
After an adviser and investor have worked together for a reasonable period of time, the investor might understand the adviser’s thinking process well enough that a simple recommendation to buy or sell a specific ETF might be accepted at once in the context of a specific investment application. Obviously, that level of acceptance will only be possible after the investor is thoroughly familiar with the adviser’s decision-making processes and has no specific questions about the proposed transaction. The investor will know that if he has a question, the adviser will have the answer and, from experience, that the answer will be fully satisfactory.
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