Random events can appear in bunches, which may make it seem like stock pattern recognition works as a strategy. But it will more likely lead you to losses

Many investors go through a time in their lives when they’re interested in market lore—observations of stock-market trading patterns that suggest easy, dependable tools for profit.

In pre-computer days, the search for stock pattern recognition took a lot of work, at least for amateurs. They had to visit a library and dig through stacks of old newspapers and other paper records to do the research. University professors had an easier way: they could assign graduate students to do the digging.

The search for profit-making guides to trading really took off after reasonably priced computers came along. Academic researchers began churning out a long string of scholarly studies on the subject.

Three research areas, in particular, attracted a lot of interest. The oldest of the three was value investing. It centres on the idea that the key to profiting is to buy stocks that seem cheap in relation to standard measures of value such as earnings, dividends and book value. Momentum trading was the next most popular. It focuses on the belief that a stock, or market, that is rising will tend to keep rising. More recently, the higher returns thought to be available from small companies (referred to as “small cap” stocks”) over big companies has gained a lot of attention.

As long-time readers know, we’ve often written about the holes in all three of these areas of belief, and why they make poor trading guides. We explained the random element in each of these factors.

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We feel you’re better off with a well-designed portfolio that has a variety of factors at work. It may include both value stocks (those with low valuations) and growth stocks (which come with high valuations). That portfolio may also include stocks that are in fashion (and are moving up as a result), along with stocks that are less popular at the moment, and as a result are lagging behind the market indexes and offer better value. It’s also likely to include both big companies and some small ones.

Stock pattern recognition research that works looking back is no guarantee of future success

A February 2019 academic paper, “A Census of the Factor Zoo,” shows how this field of research has grown. The authors are Campbell R. Harvey of Duke University and Yan Liu of Purdue University.

The abstract of the paper begins, “The rate of factor production in the academic research is out of control. We document over 400 factors published in top journals. Surely, many of them are false.” The paper explains the incentives that lead to factor mining (also known as back-testing). This tends to pump up investor expectations. Investor disappointment generally follows.

The 400 factors may seem like a stretch. However, every one of these supposed market-beaters could serve as the inspiration for a new exchange traded fund, or ETF.

In late August 2020, The Wall Street Journal reported that 188 exchange traded products had been shut down so far that year, mainly for lack of investor interest. That was about 10% of the 2,000 or so exchange-traded products in the U.S. Product fatigue hit big and small asset managers, alike. Meanwhile, today, the ETF industry, which launched in 1992, manages a healthy $10 trillion in investor funds.

Random events can appear in bunches—which may make it seem like stock pattern recognition works

Market lore can make interesting and worthwhile reading. It won’t bring you any direct or immediate financial benefit, but it can expand your investor knowledge. One of the key things you’ll learn is that studies of market factors only show what happened within specific start and end dates. Often these dates are chosen because that was a time when the factor seemed to have the desired effect.

The effect is likely to be less pronounced if not absent in studies of different and/or longer periods. Our view is that most stock-market trading patterns, if not virtually all, turn out to be examples of the fact that random events tend to occur in bunches.

Use our three-part Successful Investor approach to pick the market’s best stocks

1. Hold mostly high-quality, dividend-paying stocks.
2. Spread your money out across most if not all of the five main economic sectors: Manufacturing & Industry, Resources & Commodities, Consumer, Finance and Utilities.
3. Downplay or stay out of stocks in the broker/media limelight.

Bonus tip: Rather than trying to learn how to predict stock trends, invest instead in the best blue-chip stocks.

The best blue-chip stocks to buy and hold in your portfolio all have one thing in common: They give you reason to believe they might be worth holding on to indefinitely.

Most of these stocks have an established business and a history of sales gains, plus some earnings, if not dividends. To put it more simply, these stocks have a clear business plan that seems to be working.

Blue chips have established their value over the long term. Like all stocks, they can fluctuate widely and many suffer in a long-term market downturn, but they offer a higher probability of long-term gains.

We feel most investors should hold a substantial portion of their investment portfolios in securities from blue chip companies. These stocks should offer good “value”—that is, they should trade at reasonable multiples of earnings, cash flow, book value and so on. Ideally, they should also have above-average growth prospects, compared to alternative investments.

What’s your preferred ratio or indicator for choosing the stocks in your portfolio?