• 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.

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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

The topics discussed in this article are aimed at seasoned professionals, as such, we have included some extra for anyone seeking out more information related to the topics above.

 

  1. As a reminder for our Financial Advisors: our models are available on a continuous basis, and most have been in production for over a decade.  If you are looking for simple, concentrated, low turnover, and tax efficient model portfolios we would like to talk with you.  KCR also offers a wide range of easy-to-use but sophisticated tools.  Our toolkits can help identify mispriced stocks with the best and worst risk/reward characteristics, estimate a stock’s duration and warn you when a company is engaging in low-quality accounting. Over the last 12 years, KCR has built and offers time-tested and class-leading products built by experienced and proven money managers for fixed to low prices.
  2. Kailash Capital Research, LLC ’s sister company, L2 Asset Management, runs market neutral, long/short, large-cap, and mid-cap long-only portfolios with a value and quality bias.  L2 employs a highly disciplined investment process characterized by moderate concentration, low turnover, high tax efficiency, and low fees. While nobody can predict the future, we believe the recent resurgence in risk-adjusted returns seen across all products is the beginning of what may be a long period where speculation is punished, and prudence and patience rewarded.

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 Research, LLC and its affiliates (collectively, “Kailash Capital Research, LLC ”) 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 Research, LLC . In preparing the information, data, analyses, and opinions presented herein, Kailash Capital Research, LLC has obtained data, statistics, and information from sources it believes to be reliable. Kailash Capital Research, LLC , however, does not perform an audit or seeks independent verification of any of the data, statistics, and information it receives. Kailash Capital Research, LLC 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. © 2021 Kailash Capital Research, LLC – All rights reserved.

Nothing herein shall limit or restrict the right of affiliates of Kailash Capital Research, LLC to perform investment management or advisory services for any other persons or entities. Furthermore, nothing herein shall limit or restrict affiliates of Kailash Capital Research, LLC from buying, selling or trading securities or other investments for their own accounts or for the accounts of their clients. Affiliates of Kailash Capital Research, LLC may at any time have, acquire, increase, decrease or dispose of the securities or other investments referenced in this publication. Kailash Capital Research, LLC shall have no obligation to recommend securities or investments in this publication as result of its affiliates’ investment activities for their own accounts or for the accounts of their clients.

November 15, 2013 |

Categories: White Papers

November 15, 2013

Categories: White Papers

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