Deconstructing Pop Culture

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Interpreting Financial Information

March 14th, 2010 by David Kronemyer · No Comments

Historical financial information about companies primarily is derived from their annual reports and Form 10-Ks filed with the U.S. Securities and Exchange Commission.  As a shareholder in various entertainment firms, over time I have compiled a collection of these documents, which I have scanned and posted as downloadable files elsewhere on this site.  To my knowledge many of these are not readily available elsewhere.  If anybody has copies of documents for missing years please scan and send them to me as .pdfs.  I then will post them with a view towards creating a more complete record.

The annual report is an imperfect source of information for evaluating a record company’s performance.  Companies constantly are redefining their operating segments, buying and selling divisions and restating previous years’ results.  Despite supposedly-uniform accounting standards and generally-accepted accounting principles (“GAAP”) each company presents its financial information differently.  In particular “record company” or “music” results almost always commingle record sales with music publishing.

These anomalies make it difficult to ferret out pertinent information and compare it year-to-year, much less company-to-company.  To address these problems partially and in the most feasible way possible I used the annual report for each separate year rather than the “historical results” section set forth in a single year’s report, which is where the restatement problem most likely is to occur.  I took special care to maximize the likelihood I was using comparable data on a year-to-year basis to the fullest extent possible.  Frequently this information is not found on an income statement but rather is buried in a footnote to the accounts.  One would think there ought to be conventions establishing rules for presenting this information but there aren’t.  This is highly annoying.  All I can say about this is that inconsistencies and discrepancies are likely to occur uniformly.

Return on Sales

Raw economic statistics in the applicable currency such as the amount of turnover and pre-tax operating income (“PTOI”) are not useful in evaluating a company’s performance and they particularly are not useful in comparing one company’s performance with that of another.  For this reason percentage-based measures are more informative.  Net sales typically is defined as gross sales less variable and fixed costs but before interest, taxes, depreciation and extraordinary items such as write-offs due to reorganizations.  Sometimes an allocation for costs incurred by the corporate group also is deducted.  Pre-tax operating income (“PTOI”) is net income from running the business.  Another roughly comparable measure used today is “earnings before income taxes, depreciation and amortization”  (“EBITDA”).

Return on sales (“ROS”) is the ratio of pre-tax operating income (“PTOI”) to sales.  Because individual divisions are wholly-owned by the parent company and their financial results are consolidated it is not possible to use other typical measures of company performance such as return on investment (“ROI”).  Return on investment is the ratio of PTOI to shareholder’s equity.  Shareholder’s equity however is not broken out by operating segment.  The same principle is true with return on assets (“ROA”).  Most balance sheets break out assets under management by business segment.  However this information is not reliable because of different accounting conventions pertaining to asset allocation, valuation and depreciation.  For example a company can exaggerate its asset base by appraising its assets unreasonably high or writing them off unreasonably slow, all the while remaining within GAAP boundaries.  This leaves ROS by default as the best available measure to use subject to these caveats.

One of the issues with ROS is that to some extent it may be one-dimensional.  For example a well-run small division in an oligopolistic market may appear to outperform dramatically a huge division with ten times the turnover constrained by more competitive trading divisions.  What’s missing is scalability.  For a company with several business segments it is interesting to evaluate segment PTOI as a percentage of total corporate PTOI, against segment revenue as a percentage of total corporate revenue.  This measure is more sensitive in that it accommodates both contribution to turnover and contribution to PTOI as independent variables.  It also is more specific in that it evaluates the opportunity cost of allocating corporate resources to one segment as opposed to another.

Not measurable by any of these formulations is what I will call “return on time” (aptly, “ROT”).  ROT asks the question: what else could management be doing instead of whatever it is doing, which potentially would add more value to the firm?  What other opportunities could management pursue, which it has foregone in favor of its present course of action?  Every business decision carries with it real-world consequences – not only in terms of the direct causal effects from having taken that decision but also because it precludes you from doing other things which, had you chosen them instead, might be even more rewarding or lucrative for the firm.  To some extent ROT is speculative as one never will know for sure.  However it is valid when assessing management decisions in an environment where several different options are available and have been deliberated thoroughly.  It also is valuable when assessing these decisions retrospectively.

Graphs and Figures

Line charts are easy to read.  They are presented temporally.  One simply cross-references specific data points, which appear at the imaginary intersection of a location on the horizontal axis (the “x” axis, which typically is for years) and one on the vertical axis (the “y” axis, which typically is for results such as ROS).  Figure 1 is an example of a line chart.  Scatter-plot charts on the other hand can be somewhat more challenging.  In this case each data point also represents a single year and appears at the imaginary intersection of the “x” axis with the “y” axis.  The data points however do not appear consecutively.

One of the advantages of the scatter-plot is that data points can be forced against an imaginary line running from the lower left-hand corner of the chart to the upper right-hand corner.  Points falling on the line mean the “x” axis data are perfectly correlated with the “y” axis data.  Points below the line in the south-west quadrant are deficient on both “y” axis and “x” axis data.  This is the worst place to be.  Points above the line in the north-west quadrant are superior on “y” axis data but deficient on “x” axis data.  Points below the line in the south-east quadrant are superior on “x” axis data but deficient on “y” axis data.  Points above the line in the north-east quadrant are superior on both “x” axis and “y” axis data.  This is the best place to be.