Nerdy Stuff Matters to Making Money!

Before we show you how quality and reasonable valuations are the breeding grounds of greatness, let’s talk about a common analytical error.

When analyzing stocks and investment strategies, using bias-free data is a basic and critical first step. For a beautiful explanation, we guide you to Teddy Koker, a researcher at MIT’s Lincoln Labs, elegant walk-through, complete with programming instructions. For those interested in a less complex example, this post is for you.

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A friend sent me the image below with the affectionate note: “Nerd, this popped up in Facebook, seems like something you would find funny.” She was, of course, correct. We will use a few bullets to go from a damage analysis of World War II planes to how survivor bias in finance creates havoc for investors.

Survivorship Bias Plane Explained – What is Survivorship Bias?

  • The red dots in the image below shows where bullet holes in WWII bombers coming back from combat were most pronounced
  • The impulse was to begin adding armor to the areas of the plane with lots of holes
  • Statistician Abraham Wald of Columbia University highlighted that the impulse was wrong: the planes that made it back, had made it back, and were survivors
  • The “right” thing to do was reinforce the areas around the engines and cockpit from enemy fire
  • Once written, does it not seem obvious that planes with bullets hitting the engines might be less likely to survive?

Survivorship Bias Plane

Source: Survivor Bias Image from Wikimedia

Survivorship Bias in Finance Fails to Make the Case for High Priced Stocks

One of our many thoughtful subscribers[1] noted that some advocates of high-priced growth stocks believed they had identified the “next Amazon.” We have brought empirical rigor to the fallacy of this thinking in our piece Who is the Next Amazon. We also used tongue-in-cheek anecdotes to debunk this nonsense in our free post Apple II Flashback – the Fantasy of Predicting the Future.

Our friend, former fund manager and current Director of Research, Roger N. asked us, “if you looked at the 50 best-performing stocks over the last 20 years, what did they look like at the beginning?” Wise in the ways of survivorship error, Roger and the KCR team believed that this selection process would produce a crop of high-priced stocks like Amazon while omitting the other poorly performing high-priced stocks 20 years ago.

We were wrong. The average returns of the 50 best performing stocks was 5,292% over the last 20 years. The chart below shows how the market’s 50 best-performing stocks over the last 20 years looked 20 years ago:

Left Four Bars:

  • If the average percentile of valuation is above the 50th percentile, it means they were cheaper than the market average
  • The 50 best performers over the last 20 years had ~average starting valuations

Right Four Bars:

  • If the percentile of quality and growth is above the 50th percentile, it means the factor was higher
  • The 50 best performers over the last 20 years had above average starting quality (ROE & Total Yield above average) and slower than average sales growth (1, 3 Year Sales Growth less than the 50th percentile)

Conclusion:

Even with the sample selection loaded with survivorship bias, the 50 best-performing stocks in the US market over the last 20 years began their journeys to greatness as firms with cheap to average valuations, above-average quality, and below-average growth rates.

Even with the Benefit of Survivorship Bias the Biggest Growth Stocks Began as Cheap Quality

This newsletter has been relentless in highlighting that the rising risks of a bear market and the possible increase in Enron-type fraud have made investing in high-quality stocks at reasonable prices more important, in our view. Enamored with glamour stocks, investors have dismissed our preference for insisting on some margin of safety when investing.

If you would like to read more about survivorship bias and how it impacts any analysis of mutual fund returns, the material available from the University of Chicago is a terrific resource.

Please see below a list of the 50 best-performing stocks in the US market over the last 20 years with basic starting and current valuations:

  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.

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

  1. Click the following to read more about asset allocation, what happened to enron

[1] Hat tip to the brilliant Roger N. for this question!!

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.

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