Top 10 issues related to the selection of Cost of Capital (COC) data

BVWireIssue #80-3
May 20, 2009

To estimate the cost of capital (COC)—what investors in a certain business interest or security expect as a future rate of return—is a “daunting task,” Robert Reilly of Willamette Management Associates told the roughly 120 attendees (and 60 webinar registrants) at the CalCPA Education Foundation’s 2009 Business Valuation conference in San Francisco this past week. 

As in prior years, this one-day confab focused on a single, cutting-edge topic, developed through several sessions and a notable array of expert speakers, among them: Roger Grabowski (COC for distressed companies); James Harrington (application of the Morningstar/Ibbotson’s data); Keith Pinkerton (capturing company-specific risk with the Butler/Pinkerton Model), Brian Brinig and Jeff Kinrich (calculating the discount rate in economic damages); and Kevin Yeanoplos (cap rates for small businesses).
Conference chair Ted Israel (Eckhoff Accountancy Corporation) noted both the depth and liveliness of the discussion this year, particularly in light of the current economic crisis and the difficult questions that now confront business appraisers and analysts in what was always a challenging task.

As Reilly remarked, “We need to extrapolate from data that we have a lot of, to derive data about which we have little to no data.” Of course, he’s talking about taking historic, public company investment and pricing data from such sources as Ibbotson/Morningstar or Duff & Phelps, Bloomberg or Capital IQ, and applying them to the “generally accepted” models such as CAPM, modified CAPM, or the Build-up method. “They are the best models and data that we have,” Reilly noted, “just not necessarily the data we wish we had.” Analysts shouldn’t “over-obsess about precision,” however.  “We can get to a very precise answer, but at the end of the day, we will still have to use our professional judgment”—now more than ever, he noted, given the continued volatility of the markets and its current “aberrational” data.

What analysts really need to focus on is identifying the concerns and questions related to the selection of COC data. “There are no right or wrong answers, necessarily,” Reilly said, just issues that analysts need to talk about and applications they need to understand. With that in mind, here is Reilly’s “short list” of the top ten issues related to COC data:

  1. Risk-free rate of return measurement
  2. Appropriate historical time period for the equity risk premium
  3. Size effect equity risk premium measurement
  4. Beta measurement—levered or unlevered
  5. Beta measurement—appropriate market proxy
  6. Beta measurement—appropriate time period
  7. Beta measurement—appropriate frequency of data observations
  8. Beta measurement—appropriate adjustment factors
  9. Industry equity risk premium measurement
  10. Company-specific equity risk premium measurement

To read more details on Reilly’s “Top Ten Conclusions” from the CalCPA conference, look for an article in a forthcoming (July 2009) Business Valuation Update

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