• A Kailash Confession
  • The (Possibly Black) Art of Peer Selection
  • Regressions & Results
  • An Enterprising Concept
  • Single Stock Examples
  • Appendix I: Regression Variables Grounded in Valuation Theory
  • Appendix II: Additional P/E Analysis

A Kailash Confession:

Kailash takes pride in our dedication to a process-driven investment discipline with human oversight. Over our first few years we noticed a critical failing in our adherence to that belief: we all routinely used peer multiples when discussing the various comparative merits of firms without applying a rigorous and conceptually sound process for selecting the peers. Professor, practitioners and programmers. Guilty. Worse, we all admitted quite readily to having done some occasional “cherry-picking” of peers to make the relative cheapness or dearness of a particular target firm look that much more interesting or unappealing. If a group as committed to process-driven solutions as ours was discussing firm values in the context of other firms’ valuations without any critical thought as to how those peers were being chosen, we saw both a problem and an opportunity. We seek to address the issue in this paper.

The (Possibly Black) Art of Peer Selection:

Kailash asks our readers to consider our confession and contemplate their own peer selection process. Analysts from both sides of the street routinely apply enormous energy to fundamental due diligence. Research reports are loaded with channel checks, survey data, input cost analysis, granular assessments of the competitive landscape and detailed analysis of how the evolution of interest rates and a firm’s average employee age might affect pension obligations. Our industry seems almost fearless in its willingness to commit time, energy and resources to digging relentlessly for even the most arcane edge around company fundamentals. Almost without exception, at the end of these reports we find the sum of this hard fought knowledge synthesized into a target price using peers, often in conjunction with a DCF (which will often use peers in the terminal value calculation). Ask the typical analyst how they went about selecting those peers, and you will often hear an explanation that, no matter how nuanced, boils down to: “I used similar sized firms within the same industry.”

Over the last six months we have made a point of subtly (and not so subtly) asking a large number of clients, “Have you ever studied the information value of peer firms’ multiples in predicting future valuation levels of target firms?” Without exception the answer has been “no.” This would seem to create the potential for a great deal of fundamental conviction to be squandered in the final inch of analysis. If you spend 100 hours working up a detailed thesis based on proprietary research to forecast some combination of revenues, margins, earnings and uses of cash, does the selection of the peers not merit a similar level of consideration?

While the authors caution that their research is the first of its kind and hence exploratory, a recent working paper, “Analysts’ Choice of Peer Companies” by Gus De Franco, Ole-Kristian Hope and Stephannie Larocque seems to support some of the concerns discussed above. The authors embark on a painstaking approach of manually pulling down and collecting peer information from actual research reports to create a database of over 2,500 report-year observations and 13,500 peers.1

Disclaimer
The information, data, analyses, and opinions presented herein (a) do not constitute investment advice, (b) are provided solely for informational purposes and therefore are not, individually or collectively, an offer to buy or sell a security, (c) are not warranted to be correct, complete or accurate, and (d) are subject to change without notice. Kailash Capital, LLC and its affiliates (collectively, “Kailash Capital”) shall not be responsible for any trading decisions, damages, or other losses resulting from, or related to, the information, data, analyses, or opinions or their use. The information herein may not be reproduced or retransmitted in any manner without the prior written consent of Kailash Capital.

In preparing the information, data, analyses, and opinions presented herein, Kailash Capital has obtained data, statistics, and information from sources it believes to be reliable. Kailash Capital, however, does not perform an audit or seeks independent verification of any of the data, statistics, and information it receives.

Kailash Capital and its affiliates do not provide tax, legal, or accounting advice. This material has been prepared for informational purposes only and is not intended to provide, and should not be relied on for tax, legal, or accounting advice. You should consult your tax, legal, and accounting advisors before engaging in any transaction.

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