The stock market is no different from any other market. The laws of supply and demand ultimately determine the price of the merchandise. If there are more buyers than sellers for a particular stock, the price of that stock will rise. If there are more sellers than buyers, the stock price will fall. 

The conventional market wisdom for many years was that the stock market, as a result of the interplay between these vast numbers of buyers and sellers, was truly “efficient.” Proponents of the efficient market theory believe that since all market participants have access to the same information about a stock, the price of a stock should reflect the knowledge and expectations of all investors. Thus, an investor should not be able to beat the market since there is no way for him or her to know something about a stock that isn’t already reflected in the stock’s price. For that reason, stock prices move in a random fashion as new information comes into the market and is quickly reflected in the stock price. 

Now, I do believe that markets are efficient, to a point. However, market efficiency assumes all market participants behave in a rational fashion all of the time. Unfortunately, the human condition (and, remember, humans ultimately decide stock prices) does not lend itself to full-time rational thinking. 

That humans behave irrationally when it comes to things financial has gained momentum in the academic world in recent years. In fact, the Nobel Prize in Economic Sciences in 2002 went to Daniel Kahneman, who isn’t even an economist. Kahneman is a psychologist who still teaches Psychology 101 at Princeton. Kahneman, along with his long-time collaborator Amos Tversky (who passed away in 1996) published a paper in 1979, “Prospect Theory: An Analysis of Decision Under Risk.” That paper formed the basis for the concept of “loss aversion”; that is, people generally derive more pain from a loss than they do pleasure from a gain. 

Kahneman and Tversky also found that individuals tend to overweight recent data in making forecasts and judgments. Think about how most decisions are made. All of us have a tendency to focus on recent information, to extrapolate the near term into the long term. This tendency helps to explain the herd mentality on Wall Street — people buy winning stocks because they expect near-term winners to be long-term winners. Or, people sell stocks everyone else is selling simply because recent data (i.e., the stock is falling in price) influences their decisions. 

A student of Kahneman, University of Chicago professor Richard Thaler, has been one of the leaders in applying behavioral psychology to the world of economics and finance. For example, Thaler has used behavioral psychology to research “contrarian” investing. Contrarian investors buy investments that are out of favor with the general investing public. Contrarians believe that if the essence of successful investing is buying stocks at cheap prices, then stocks that are being shunned by investors should represent the stocks offering the best value. 

Contrarian investment strategies are successful because they take advantage of investor overreaction. This overreaction, so say behavioral psychologists, is partly a result of investors making bad projections about stock prices as a result of overweighting recent events. Of course, buying a stock that has fallen sharply won’t make you any money if it stays down forever. That’s where the second important piece of the puzzle comes into play. Contrarian investors also depend on the concept of “mean reversion.” 

Think for a moment about the world around you. Things — weather patterns, people’s emotions, even societal behavior — tend to track some equilibrium range, a steady state, if you will. Occasionally, this steady state gets disrupted. In the case of weather, you have tornados and hurricanes and floods. In the case of societal behavior, riots and looting. In the case of human emotions, the peaks and valleys caused by big events (marriage, children, death). Thus, in the short run, things have the ability to run to extremes. Over time, however, things tend to revert to the equilibrium state, the long-run average. Things can’t help but revert to the average, the mean, over time. Indeed, it requires too much energy for things to stay at the extremes. As the energy that created the extremes (think wind for hurricanes) dissipates, things tend to revert to their steady state. 

A good analogy for mean reversion is a rubber band. A rubber band can stretch and contort when pressure is applied. Once the pressure ceases, however, the rubber band returns to its steady state. Mean reversion has important implications for investing, especially contrarian investing. Contrarians believe that if you buy stocks that have run to extremes on the downside (or sell stocks that have run to extremes on the upside), you will eventually be rewarded when mean reversion returns the stocks to their long-run equilibrium price level. 

To be sure, mean reversion/ contrarian investing is not as simple as going out and buying any beaten-down stock. For example, the last thing a contrarian wants to do is buy a cheap stock that gets cheaper and cheaper and cheaper and then becomes extinct. Bankruptcy is the bane of any contrarian investing strategy. Bankruptcy steals the time a stock needs to revert to its mean. For that reason, stocks that seem best situated for a mean-reversion strategy are large, seasoned, time-tested companies with sound finances and the ability to weather down cycles in the economy and stock market. When these stocks show extreme price declines, especially relative to some appropriate benchmark, smart investors buy. 

How do my worst-to-first investment strategies fit into this more contemporary view of the investment world? Rather well. My worst-to-first strategies focus exclusively on buying beaten-up, blue-chip issues in the Dow. These are the type of companies that have demonstrated over many decades the sort of financial firepower and staying power that make them well suited for a mean-reversion investment strategy. 

Another reason my worst-to-first strategies make sense in today’s investment environment is that the strategies’ investment methodology relies solely on one data point — a stock’s 12-month percentage price change. This data point cannot be fudged, obfuscated, or manipulated. A stock’s price change is an absolute. The same can’t be said for revenue, net income, debt, or any other investment metric found on the balance sheet or income statement. As we’ve seen in recent years, corporate America is not above employing fuzzy accounting or even downright fraud to distort or puff these numbers. 

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