One of the most common misconceptions about the interpretation of price movements of charts is the expectation that pattern recognition equals precise predictability. While one aspect of using technical analysis is to make sense of price movements, there is no certainty that what has worked in the past will work in exactly the same way every time in the future. The task of interpreting price movements is an attempt to gauge the collective activity of a large population of investors with many different goals, essentially gauging crowd behavior.
A basic tenet of chart analysis is that the common human traits of fear and greed transcend time and that this knowledge can be used to create predictive forecasts for price behavior. What does change, are the conditions of the markets and the absolute ranges of fear and greed. Thus, while we can with some confidence, determine the path of prices of stocks in general, it is not always easy to isolate the activity for any particular issue.
We’ve often heard that “if you had invested X dollars in the Dow Jones in 1960, your stake would be worth some large multiple of X today” hence validating the notion of long term investing. While this is true, the reality is that many components of the Dow Jones have changed over the past few decades and some of those venerable Dow components such as Westinghouse and General Motors are no longer in the Dow Jones or have ceased to exist. The Dow Jones 30 is supposed to represent the top industries influencing the American economy and as we know, former smokestack businesses such as the aforementioned Westinghouse as well as US Steel, no longer dominate American business. This holds true for the benchmark Standard & Poor index as well.
Now, companies such as Apple and Microsoft are the dominant titans of American industry. So the yardstick of the Dow Jones is not of American companies so much as they are representatives of successful American companies. At a recent professional MTA symposium that I attended, there was an insightful presentation by Thomas Lee, the founding principal of Fundstrat Global Advisors, that revealed some interesting statistics of which most market participants are likely unaware.
In essence, he showed that in every market cycle, there were only a handful of stocks in new dynamic industries that were responsible for most of the returns of equity investors. In other words, being able to isolate those companies or industries of outperformance in a demographic cycle would yield returns far and above that which could be obtained by being invested in the market averages.
To illustrate his point, he showed two periods of growth in the equity markets, both closely tied to the demographic influences of the particular era. In the first era, under the influence of the baby boomers, consumer stocks were the most dynamic vector, therefore investments in Wal Mart, Circuit City, Hasbro, Home Depot, Gap, Limited Brands and Dillards dominated market movement. In the era from 1980 to 2000, those top consumer companies returned 1171x on investments whereas the S&P, while bullish, returned only 16.2x! In fact, he notes that in a basket of 100 consumer stocks, 93% could go to zero and you would still get a 12x return!
In a similar vein, the modern demographic era, that of the Gen X, the stars have been the so called FANG stocks. Measured from 1997 to now, the FANG stocks have a 1567x statistic while the S&P returned 3.6x during this time. Doing the same comparison as for the baby boom era, a basket of 100 internet stocks in which 96% went to zero would still have yielded a 16x return!
Lee illustrates the point very well, that while being invested in the stock market has been beneficial, the real returns are to be made by isolating those companies which ride the demographic wave in any era. He postulates that now, determining the spending habits of Millennials will be the key to relative outperformance in the stock markets going forward.
This underscores the power of performing relative strength analysis and even of pedestrian trend following techniques. Such outperforming companies are not hard to find, they are often in the news as their influence on our lives grows. At the moment, the emerging dynamic industries are in alternative power, digital currencies and online retail.
There is another reason why this ‘rotation’ is important. It means that markets may not collectively move lower under a ‘topping’ scenario as many pundits have called for. Certainly excesses will be wrung out but as we’ve seen from previous demographic eras, there will always be new winners which will separate from the pack. The stock market is dynamic and even as some companies falter, others will rise in their place. As the classic wisdom states, the market is not reflective of actuarial value, it is a predictor of future action and thus discounts known information. The winners of today will likely not be the winners of tomorrow.
The tricky part is that the stock market is very much a reflection of mass crowd behavior. As with all crowds, they will move to extremes in both enthusiasm and fear under certain conditions. While trends can be discerned, individual vectors can appear random and subject to misinformation. Using the relatively simple tool of relative strength is one of the best ways to sort out the randomness. It also aids in determining where the crowd is placing their money.
As we’ve seen, exposure to the stock market has been good, but knowing where the outperformers may lie is even better.