Now and then, I hear someone say that stock market investing is gambling. Is this true or false?
A good friend of mine, with the stock trading alias of the Lone Ranger, told me that her relative said investing in Penny Stocks is gambling.
Gambling is, by definition, the activity or practice of playing a game of chance for money or other stakes.
Let’s take a step back, this implication, that investing in the stock market is gambling, is often a sentiment expressed by people who believe that making money is not likely. The result for most people will be a loss. Furthermore, there may be little basis for a sound investment in some stocks, such as penny stocks, since investing theory indicates that a company’s financials may not be in line with a sound business model.
The points above are somewhat reflected in the paper titled, “Who Gambles in the Stock Market?” by Alok Kumar.[1]
In the paper, Kumar identifies lottery-type stocks by using lottery tickets (the most common form of gambling) as a reference. Lottery tickets have very low prices relative to a high potential payoff. They have low negative expected returns, and the prize distribution has exceptionally high variance. Most importantly, they have a minuscule probability of a huge reward and a huge chance of a small loss.
To identify lottery-type stocks, Kumar characterizes stocks with low prices, high volatility, and investor sentiment skewness. The author has more precise terms that many people have never seen before.
For example, he uses the term idiosyncratic volatility where Investopedia defines idiosyncratic risk in the following way:
“Idiosyncratic risk refers to the inherent factors that can negatively impact individual securities or a very specific group of assets. The opposite of Idiosyncratic risk is a systematic risk, which refers to broader trends that impact the overall financial system or a very broad market.”[2]
In other words, there may be high volatility of oil company security due to pipeline breaks. This may result in an adverse price move. Conversely, if a large oil field is discovered, this may cause a positive price move. The result is the high volatility of the stock price. When these events happen for a particular company more than once, there may be a skewed perception of the company unrelated to the company’s fundamentals. People may invest in them thinking that the large moves will happen again, especially if it’s a low priced stock, AKA Penny Stock.
Interestingly enough, Kumar’s paper does have a table that characterizes lottery-type stocks. Table 2, titled Basic Characteristics Of Lottery-Type Stocks, reports that there are 1500 lottery-type stocks, 1500 non-lottery-type stocks, and 9000 stocks in the middle.
So what are the characteristics of a lottery-type stock?
The table reports that the firm size average is very low with an average market capitalization of 31 million, low institutional ownership at 7.35%, a relatively high book to market ratio 0.681, and lower liquidity. These stocks are also younger, with a mean age of about six years. They have low analyst coverage, most don’t have dividends, they have significantly higher volatility, higher skewness, and lower prices.
The author goes on to report that lottery-type stocks are concentrated heavily in the energy, mining, financial services, biotechnology, and technology sectors and the lowest concentration of lottery stocks is in the utilities, consumer goods, and restaurant sectors.
Given the fact that there are lottery-type stocks and non-lottery-type stocks, how likely, in general, is a trader or investor to make money in the Stock market? Remember the sentiment we discussed earlier, that most people lose money in the stock market, which is similar to the feature of lottery tickets with their negative expected return.
According to the Tradeciety:
“Profitable day traders make up a small proportion of all traders – 1.6% in the average year. However, these day traders are very active – accounting for 12% of all day trading activity.”[3]
That doesn’t sound encouraging, but this may be a problem with trading frequently.
What about the long term, buy and hold investing as Warren Buffett does? His favorite holding period is forever.[4]
I made the most money in the stock market in paper gains when I picked outstanding diversified funds, ignored them when the market was misbehaving, and held them long term. Many famous investors have made money through the buy and hold strategy, such as Warren Buffett, Jack Bogle, John Templeton, Peter Lynch, and Benjamin Graham.
In my opinion, market fluctuations are unpredictable most of the time. Sometimes you can see the writing on the wall; for example, the Corona crash seemed evident in my opinion. The virus itself was a surprise, though, and so was the financial crash of 2008.
The market has something going for it that favors long term investing. This may end someday, but historically the market goes up over time and always recovers from a crash. (We are almost out of the Corona Crash with the S&P and NASDAQ making new highs. We are waiting on the DOW which is close). In my book Crash Proof Your Investment, I developed a historical histogram chart that shows this favoritism.
The vertical axis may look confusing. What does it mean?
I calculated the rolling annualized returns by using one year of data. But the annual return is calculated for each market day, so the one year of data slides like a window to collect a new day and dispense of an old one. There were 251 trading days in 2018, which means there are 251 annual return values.
Over 105 years, there are about 26,355 (251 x 105 = 26,355) annual return values.
The horizontal axis depicts the annual percentage gain. By looking at the 0 percent annual bar, you can see that 0 percent annual return happened a little less than 3,000 times in 105 years.
Disappointing returns for the long investor!
More importantly, the graph shows that the market has positive returns more frequently because the bulk of the bars in the graph are above 0 percent annual return.
The market is skewed! Five percent, ten percent, and fifteen percent annual returns are the most frequent.
There are even some outliers at a 70 percent annual return and above.
To put these numbers in perspective, let’s answer the question: How long will it take an investment to double in the market?
The average return was 9 percent? If we assume that is the fixed rate of return for every year that the investment is in the market, then we can use the Rule of 72 to answer the question.
The Rule of 72 is an equation that provides you with the length of time an investment will take to double. In our case we would divide 72 by our fixed rate of 9.
Our answer shows us it will double every eight years. Impressive!
If the graph is still confusing, there is still hope. Check out the excellent article on Investopedia called “Rolling Return.”[5]
A more familiar chart is the one shown below:
The trend is undoubtedly up. So this indicates that there may be something to buy and hold for the long term.
Finally, from the paper by Kumar, four-factor models for the stock market return are mentioned. A somewhat simplified explanation of this model is in the Investopedia article titled, Fama and French Three-Factor Model[6]. The article states that:
“Nobel Laureate Eugene Fama and researcher Kenneth French, former professors at the University of Chicago Booth School of Business, attempted to better measure market returns and, through research, found that value stocks outperform growth stocks. Similarly, small-cap stocks tend to outperform large-cap stocks. As an evaluation tool, the performance of portfolios with a large number of small-cap or value stocks would be lower than the CAPM result, as the Three-Factor Model adjusts downward for observed small-cap and value stock out-performance.”[7]
Later on the article reports:
“Fama and French highlighted that investors must be able to ride out the extra short-term volatility and periodic underperformance that could occur in a short time. Investors with a long-term time horizon of 15 years or more will be rewarded for losses suffered in the short term. Using thousands of random stock portfolios, Fama and French conducted studies to test their model and found that when size and value factors are combined with the beta factor, they could then explain as much as 95% of the return in a diversified stock portfolio.”[8]
So as you can see from the Investopedia article and the work of Fama and French, long term investing offsets short term losses that a day trader or short term trader might experience.
In the book Intelligent investor, which is one of the seeds of Warren Buffett’s massive fortune, there is commentary from Zweig’s section that says
“Like casino gambling or betting on the horses, speculating in the market can be exciting or even rewarding (if you happen to get really lucky). But it’s the worst imaginable way to build your wealth. That’s because Wall Street, like Las Vegas or the racetrack, has calibrated the odds so that the house always prevails, in the end, against everyone who tries to beat the house at its own speculative game.
On the other hand, investing is a kind of a unique kind of casino—one where you cannot lose in the end, so long as you play only by the rules that put the odds squarely in your favor. People who invest make money for themselves; people who speculate make money for their brokers. And that, in turn, is why Wall Street perennially downplays the durable virtues of investing and hypes the gaudy appeal of speculation.”[9]
In summary, we have discovered that there are lottery-type stocks that resemble gambling in the stock market and there are investing strategies where the outcome is more likely to be profitable. So investing in the stock market is not gambling—keyword investing. But there are plenty of opportunities to gamble with securities in the stock market. These tend to be, but are not limited to, penny stocks.
That’s all for now; good luck with your financial goals,
Dr. Paul Keller.
The Beginner’s Guide to Rental Property Investing
[1]Kumar, Alok. “Who Gambles in the Stock Market?” The Journal of Finance 64, no. 4 (2009): 1889-933. Accessed September 14, 2020. http://www.jstor.org/stable/27735154.
[2] https://www.investopedia.com/terms/i/idiosyncraticrisk.asp
[3] https://www.tradeciety.com/24-statistics-why-most-traders-lose-money/
[5] Chen, J. (2020, January 29). Rolling Returns Definition. Retrieved from https://www.investopedia.com/terms/r/rollingreturns.asp.
[6] https://www.investopedia.com/terms/f/famaandfrenchthreefactormodel.asp
[7] https://www.investopedia.com/terms/f/famaandfrenchthreefactormodel.asp
[8] https://www.investopedia.com/terms/f/famaandfrenchthreefactormodel.asp
[9] Benjamin Graham, Intelligent Investor.
Campbell, M. (2018, February 03). What Warren Buffett Really Means When He Says His Favorite Holding Period Is “Forever”! Retrieved September 14, 2020, from https://www.montycampbell.com/article/what-warren-buffett-really-means-when-he-says-his-favorite-holding-period-is-forever/
Chen, J. (2020, April 23). Idiosyncratic Risk: Why a Specific Stock Is Risky Right Now. Retrieved September 14, 2020, from https://www.investopedia.com/terms/i/idiosyncraticrisk.asp
Graham, B., & Zweig, J. (2003). The intelligent investor: A book of practical counsel. NY, NY: HarperBusiness.
Hayes, A. (2020, March 05). Fama and French Three Factor Model Definition. Retrieved September 14, 2020, from https://www.investopedia.com/terms/f/famaandfrenchthreefactormodel.asp
Hayes, A. (2020, March 05). Fama and French Three Factor Model Definition. Retrieved September 14, 2020, from https://www.investopedia.com/terms/f/famaandfrenchthreefactormodel.asp
Hayes, A. (2020, March 05). Fama and French Three Factor Model Definition. Retrieved September 14, 2020, from https://www.investopedia.com/terms/f/famaandfrenchthreefactormodel.asp
Kumar, Alok. “Who Gambles in the Stock Market?” The Journal of Finance 64, no. 4 (2009): 1889-933. Accessed September 14, 2020. http://www.jstor.org/stable/27735154
Rolf, Witbooi, Mataruse, M., Sm, Anonymous, Burguet, M., & Ahmad. (2020, April 10). Why Most Traders Lose Money – 24 Surprising Statistics. Retrieved September 14, 2020, from https://www.tradeciety.com/24-statistics-why-most-traders-lose-money
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