AgPa #15: Concentrated Stock Markets (6/7)

Extreme Stock Market Performers, Part I: Expect Some Drawdowns (2020)
Hendrik Bessembinder
SSRN Working Paper, URL

This is the sixth of seven AGNOSTIC Papers on the extreme concentration in stock markets and the last one on the characteristics of the few big winners. But before we go into the analyses, let’s try to do the following thought-experiment. Suppose you applied all insights of the last papers and identified Amazon as one of the most likely top-performer in 1997. The question now becomes: can you hold it over the long-term without knowing what you know today?[1]It’s basically impossible to ignore that, but it’s a good exercise. Although this sounds straight-forward, I will argue that it was probably not that easy for most people.

Amazon’s stock price collapsed by more than 90% in the dotcom-crash, by more than 60% during the financial crisis 2008, and by more than 30% just recently in 2022. Of course we know today that it came back stronger than before (at least in two of the three cases). However, living through a 90% drawdown is no fun. Especially not when the stock makes up a large fraction of your portfolio. This week’s paper shows that such pain is part of the deal. Even the best-performing stocks had some bad crashes that tested investors’ conviction. Without the ability to take short-term pain, it’s almost impossible to capture the long-term performance of the big winners.

As always, I bore you with the recommendation to read the posts of this series chronologically. But feel free to use the following list to do whatever you want.

  • Week 1: Concentration in the US Stock Market between 1926 and 2019
  • Week 2: Concentration in Global Stock Markets between 1990 and 2019
  • Week 3: Dominance of the Tech-Industry?
  • Week 4: Characteristics of Big Winners?
  • Week 5: Identifying Big Winners Upfront?
  • Week 6: Even Big Winners had Bad Drawdowns
  • Week 7: The Same Pattern for US Mutual Funds

Everything that follows is only my summary of the original paper. So unless indicated otherwise, all tables and charts belong to the authors of the paper and I am just quoting them. The authors deserve full credit for creating this material, so please always cite the original source.

Data and Methodology

The data is the same as for the last three papers. The author uses stock market data from CRSP to construct a sample that includes 26,285 US companies between 1950 and 2019. So it is very similar to the US sample of the original paper. Since price data is sufficient to calculate drawdowns, this one is less complicated because there is no need for fundamental data.

The author again calculates Shareholder Wealth Creation (SWC)[2]SWC measures the total wealth that a company creates over its lifetime in excess of risk-free treasuries. Most importantly, it accounts for the fact that dividends cannot be reinvested in aggregate. Therefore, it takes the perspective of a hypothetical investor who owns the entire company. for the seven calendar-decades between 1950 and 2019 and identifies the best-performing companies over the entire sample period. Subsequently, he calculates the maximum drawdown of the top wealth-creators during their successful decade and the decade before. Unfortunately, he doesn’t look at the top performers in terms of total returns in this paper. This would have been also interesting.

Just as a reminder: drawdowns measure the distance from the current stock price to it’s previous peak in percent.[3]The previous peak is also known as High Water Mark. For example, the S&P 500 reached an all-time-high of 4,796 at January 3, 2022. At the last price of 4,130 on July 29, the current drawdown is thus 13.9%.[4]4,130 / 4,796 – 1 = -13.89% The lowest price for 2022 was 3,667 on June 16, so the maximum drawdown for this year (so far) was 23.5%. Since the index hasn’t reached it’s previous high, the current drawdown is not yet finished and is now running for about 7 months.

I guess it’s quite obvious that nobody likes long and deep drawdowns. Therefore, they are commonly used as one measure for the risk of an investment. I find them quite useful because they are intuitive and much easier to understand than volatility. The maximum drawdown simply tells you the largest historic loss of a particular investment and, if it managed to do it, how long it took to recover.

Important Results and Takeaways

Even the best companies during their best decades had substantial drawdowns

The following table shows the top 50 wealth-creators across different decades.[5]For brevity, I have only included the top 50 wealth-creators. The original table in the paper lists the top 100. Therefore, the same company may appear multiple times. The four columns on the right show information about the maximum drawdown of the company during it’s successful decade. This is the most important point. Those are the drawdowns of the most successful companies during their most successful decade. So it’s a very curated sample and yet some drawdowns are substantial.

Excerpt of Table 1 of Bessembinder (2020). The excerpt shows the first half (top 50 wealth-creators) of the original table in the paper.

The magnitude for some companies is impressive. For example, despite its tremendous wealth-creation between 2010 and 2019, Apple had a 9-month-drawdown of almost 40% between September 2012 and June 2013. And this is even relatively modest. The worst drawdown for the Bank of America was 69.31% and took almost two years (20 months) to recover. However, there are also companies with modest drawdowns of around 20% and very quick recoveries.

The average drawdown for the top 100 wealth creators was 32.5% and lasted for 10 months. So even if you successfully identified the top 100 wealth-creators during their successful decades, you must have been willing to lose about a third of your money for almost one year. On average. Sometimes it was much worse.

I repeat myself, but remember that this is a very curated sample. Those are the top wealth-creators and we know in hindsight that they survived their drawdowns. But living through a drawdown in real-time is very different because nobody can tell you if your money will ever come back. Therefore, successful investments require both the analytical capability to identify the big winners, and the psychological stamina and conviction to live through periods of pain.

Today’s drawdowns of tomorrow’s winners are even worse

The structure of the next table is identical, but now the last four columns show maximum drawdowns of the top 50 wealth-creators during the decade before they became so successful. As I already mentioned last week, future winners tend to be difficult stocks today. The maximum drawdowns show this again very clearly.

Excerpt of Table 2 of Bessembinder (2020). The excerpt shows the first half (top 50 wealth-creators) of the original table in the paper.

I already mentioned the extreme 91%-drawdown of Amazon in the introduction. But the company isn’t alone with such dramatic numbers. For example, in the decade before it’s great run, Apple lost 79.18% and required 3 years to recover the losses. Even more striking, Microsoft needed almost 9 years to recover it’s drawdown of 63.44% after the dotcom crash. Nine years until break-even is quite a long time.[6]Of course, very few investors bought at the absolute all-time high. Therefore, each investor needs to calculate her own drawdown based on her specific entry-price. That said, I still believe that many Microsoft-investors of the early 2000s waited many years for the recovery or even sold before they reached it.

Overall, the average drawdown for the top 100 wealth-creators in the decade before their successful decade was 51.6% and lasted for 22 months. This once again highlights that future wealth-creators are very difficult stocks before they get successful. But to fully capture the outstanding performance, investors must live through those earlier periods of pain.

Conclusions and Further Ideas

I know this posts reads somewhat cautious and admonishing. Believe me, I don’t want to be the academic who lectures you that picking stocks is hopeless anyway and that you should just stop doing it.[7]That said, I do believe that many people who pick stocks shouldn’t do it. However, I do want to stress the point that picking the right stock (which is very difficult for itself) is only half of the story. Even with the best companies during their best decades, the road to success is anything but smooth. At least historically, there were painful drawdowns that sometimes lasted for years. But to capture the outstanding performance of big winners, investors need the conviction to live through such periods. This isn’t fun and might actually be harder than identifying the right stock.

Since this is the last post on the characteristics of big winners, let me try to summarize the results. Despite some (more or less) robust statistical patterns, there is unfortunately no holy grail to identify big winners. Sadly, it is equally difficult to avoid the biggest losers. But since both problems are literally like searching a few needles in a large haystack, those conclusions are not really surprising to me.

The good news is that there are outstanding companies in all industries, although the odds are slightly better in some of them. The bad news is that industries are therefore not really helpful to narrow the search. Outstanding stock performance usually comes with outstanding fundamental performance. So fundamentals are definitely important, but still explain relatively little. Fundamentals are also somewhat useful to identify big winners ex-ante. However, even with a lot of control variables, the explanatory power is limited. Finally, the success of the few big winners is very obvious in hindsight, but very messy in real-time. They suffered the same or even worse short-term losses like other stocks and sometimes needed years to recover. I leave it to everyone for him- or herself to decide what to do to with those results.

Next week, I will conclude this series with one additional out-of-sample test. And as it turns out, individual stocks are not the only asset class with fairly concentrated long-term returns.

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