Though the Market Is a Winner, Most Stocks Are Losers

The U.S. “stock market” is represented by various collections of stocks, such as the Dow Jones Industrial Average (30 stocks), the NASDAQ Composite (securities listed on the NASDAQ; weighted towards information technology), and the Standard and Poor’s 500 Index. The S&P 500 is an index of the largest 500 companies listed on the New York Stock Exchange and the NASDAQ, weighted by capitalization. The version of the S&P usually cited just takes into account stock prices. History shows that, over a reasonably long-time frame, the U.S. stock market rises. Here is a chart, using a logarithmic axis, of the S&P from January, 1950 to February, 2016. It shows a rise in value by a factor of about 65 between 1950 and 2016.

S&P 500 daily closing values from January 3, 1950 to February 19, 2016

Below is a chart of S&P values from 1980 to 2021 on a linear scale, which compresses the earlier data and magnifies more recent variations. This shows the Covid-related dip in early 2020, which was followed by a meteoric rise as Fed and federal money flooded the financial system:

Source: Yahoo Finance

A lab technician I knew in my company in the 1990s took every bit of savings he had (about $50,000) and plowed it all into the stock of America Online (AOL). This was when the internet was just taking off, and AOL was a leading company in that field. My friend held on while his investment doubled, then had the conviction to hang on until it doubled again. He then cashed out with around $200,000, quit his job, got an MBA in finance, and ended up managing money on Wall Street.

With these sorts of success stories, and the (so far) reliable performance of the stock market, how hard can it be for the average small investor to pick a winning basket of stocks? Surprisingly hard, it turns out.

A study of the returns of U.S. stocks from 1926 to 2015 was published by Hendrik Bessembinder, a business professor at Arizona State University. A draft copy is here . He worked with total returns (stock price plus dividends). He found that the rise of the S&P is entirely due to huge gains by a tiny subset of stocks. The average stock actually loses money over both short and long time periods. In statistical terms, this is an extremely skewed data set; the mean return is greater than the median. There is a sort of Darwinian selection that occurs in a market index like the S&P 500. The companies that are doing well tend to get more represented in the index as their stock prices rises relative to other companies, while the relative weighting of losers automatically diminishes.

This asymmetry between winners and losers is partly a result of the following math: If you invest $1000 in a company that then tanks, the most you can lose is $1000. But if that company is one of the rare firms that really takes off, you could make many times your initial investment. If you had put $1000 into Microsoft (MSFT) in 1986, your shares would now be worth nearly  five million dollars.

According to Bessembinder’s study, half of the U.S. stock market wealth creation had come from a mere 0.33% of the listed companies. The top five companies (ExxonMobil, Apple, GE, Microsoft, and IBM, at that point) accounted for a full 10% of the market gain. Each of these companies had created half a trillion dollars or more for their shareholders. ( A similar list of the top five or ten value-creating companies drawn up in 2021 would have a different set of names, obviously, but a similar principal has held in recent years – a huge portion of the rise in “stocks” in the past five years has been due to a handful of internet superstars, the FAANGM stocks).

Out of some 26,000 listed companies, 86 of them (0.33%) provided 50% of the aggregate wealth creation, and the top 983 companies (4%) accounted for the full 100%. That means the other 25,000 companies netted out to zero return. Some gave positive returns, while most were net losers.

The average stock which you might pick by throwing darts at the Wall Street Journal listings lost money 52% of the time in any given month, and 51% of the time over the life of the company. The lifetime of the average company was only seven years, with only 10% of companies lasting more than 27 years.

This helps explain why actively managed stock funds, where diligent experts analyze and select some subset of stocks in an attempt to beat the market, typically underperform the broad market indices. (The fees charged by these funds also drags down their performance relative to the market indices). This also explains why about half the small-cap stocks I have bought over the years in my little recreational brokerage account have lost money. I had thought I was particularly inept at stock-picking. Turns out I was just about average.

Avoiding Intertemporal Idiosyncratic Risk

Hopefully by this time we all know about index funds. The idea is that by investing in a large, diversified portfolio, one can enjoy the average return across many assets and avoid their individual risk. Because assets are imperfectly correlated, they don’t always go up and down at the same time or in the same magnitude. The result is that one can avoid idiosyncratic risk – the risk that is specific to individual assets. It’s almost like a free lunch. A major caveat is that there is no way to diversify away the systemic risk – the risk that is common across all assets in the portfolio.

We can avoid the idiosyncratic risk among assets. But, we can also avoid idiosyncratic risk among times. Each moment has its own specific risks that are peculiar to it. Many people think of investing as a matter of timing the market. However, people who try to time the market are actively adopting the specific risks that are associated with the instant of their transaction. This idea seems obvious now that I’m writing it down. But I had a real-world investing experience that– though embarrassing in hindsight – taught me a heuristic for avoiding overconfidence and also drilled into my head the idea of diversifying across time.

I invested a lot into my preferred index fund this past year. I’d get a chunk of money, then I’d turn around and plow it into the fund. What with the Covid rebound, it was an exciting time. I started paying more attention to the fund’s performance, identifying patterns in variance and the magnitude of the irregularly timed and larger changes. In short, by paying attention and looking for patterns, I was fooling myself into believing that I understood the behavior of the fund price.

And it’s *so* embarrassing in hindsight. I’d see the value rise by $10 and then subsequently fall to a net increase of $5. I noticed it happening several times. I acted on it. I transferred funds to my broker, then waited for the seemingly regular decline. Cha-ching! Man, those premium returns felt good. Success!

Silly me. I thought that I understood something. I got another chunk of change that was destined for investing. I saw the $10 rise of my favorite fund and I placed a limit order, ensuring that I’d be ready when the $5 fall arrived. And I waited. A couple weeks passed. “NBD, cycles are irregular”, I told myself. A month passed. And like a guy waiting at the wrong bus stop, my bus never arrived. All the while, the fund price was ultimately going up. I was wrong about the behavior of the fund. Not only did I fail to enjoy the premium of the extra $5 per share. I also missed what turned out to be a $10 per share gain that I would have had if I had simply thrown in my money in the first place, inattentive to the fund’s performance.


I hate making bad decisions. I can live with myself when I make the right decision and it doesn’t pan out. But if I set myself up for failure through my own discretion, then it hurts me at a deep level. What was my error? Overconfidence is the answer. But why did it hurt me?

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