A couple of weeks back, Financial Times published an article titled Past Performance Is a Public Enemy. To support that assertion, the author showed that, over the past 20 years, stocks that led the US equity charts in a given calendar year rarely repeated the feat during the next year. In fact, they tended to trail the averages.
That’s a fine warning for new investors who are tempted by Nvidia’s NVDA success, but not, I think, of much use to this column’s readers, most of whom learned long ago that trees do not grow to the sky. Also, the evidence is sorely incomplete. There are many ways to attempt to use stock prices to forecast future returns besides comparing calendar-year performances.
Happily, academic researchers have studied this topic for decades. This column will summarize their findings, when addressing the following question: Should one ignore past stock market returns when investing, as the Financial Times author stated, or can such information sometimes be useful?
Stage 1: Short-Term Prices
Almost 60 years ago, future Nobel laureate Eugene Fama debunked the promises of stock market chartists. In a landmark paper called The Behavior of Stock-Market Prices, Professor Fama demonstrated that “the series of price changes [among individual stocks] has no memory, that is, the past cannot be used to predict the future in any meaningful way.”
The academic community quickly embraced the paper, as it had long considered technical analysis to be a modern form of reading tea leaves, following astrology, or interpreting entrails. Its finding was, however, less universal than was initially believed. Fama had only considered daily movements (and for a limited number of stocks over a limited period, at that). Changes in equity prices could well be random over 24 hours but predictable over longer periods.
Stage 2: Long-Term Prices
Which, two decades later, another future Nobel laureate documented. In Does the Stock Market Overreact?, Richard Thaler and his co-author, Werner De Bondt showed that, when extending the analysis from one day to three years, the outcomes dramatically changed. This time, past performance truly was meaningful, as portfolios formed by buying the previous 36 months’ losers cumulatively outgained the overall stock market by almost 20 percentage points, while portfolios formed by the winners trailed the averages.
As the authors themselves admitted, their exercise tipped its hat to legendary value investor Ben Graham. Not directly, as Graham picked stocks by studying financial statements, while Thaler and De Bondt skipped the hard work by simply selecting the worst recent performers. But the two methods largely reached the same place by identifying cheap, unpopular companies.
Professor Fama was so taken aback by the paper’s results that he hired a graduate student to duplicate its research. The numbers checked. In hindsight, he should not have been so startled. Although it stood to reason that investors should not be able to outgain the market by using mechanical rules, the academic community had not properly tested that thesis. Instead, they had studied the single aspect of daily prices, and then generalized that finding.
After some reflection, the efficient-market theorists realized that the Thaler/De Bondt finding could be explained. True, value stocks had earned above-market returns, but that was no free investment lunch. Those stocks were cheap because their companies were risky. Either their operations were distressed or their balance sheets indebted. It was therefore rational that their long-term gains were higher. More risk, more reward.
Stage 3: Intermediate-Term Prices
Eight years later, another seminal paper crashed the defenses of the efficient-market hypothesis. Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency, by Narasimhan Jegadeesh and Sheridan Titman, evaluated a third possible time frame, by examining stock price changes over three- to 12-month periods. Longer than Fama, shorter than Thaler/De Bondt. These computations, too, uncovered a relationship.
But on this occasion the effects were quite different. Whereas Thaler/De Bondt’s 36-month analysis showed that losers became winners (and vice versa), the reverse occurred in the Jegadeesh/Titman paper. Long-short portfolios created by owning the biggest winners of the past six months and by selling the biggest losers earned an annualized 12% return when held over the next six months. The outcome was what the Financial Times article stated, but in the opposite direction!
Once again, academic researchers had modeled a common investment strategy—what was then termed relative strength—and once again they discovered, to the professors’ surprise, that the sorcery succeeded. This time, there was no straightforward interpretation. Although efficient-market theorists have offered various justifications for this odd result, their explanations have not been widely accepted, even among finance Ph.D.s.
These are but the major items. During the three decades that have passed since the Jegadeesh/Titman study was published, scores of papers have documented additional “anomalies.” While less sweeping than the value and momentum discoveries, they nonetheless have further eroded the notion that stock market price changes are a pure “random walk.“
The Value of Historical Stock Market Returns: Final Thoughts
The FT headline to the contrary, considering past stock market performance when making investment decisions is not necessarily foolish. Stock price changes can be material. Sometimes the correlation between the past and future is positive, with gains begetting more gains, and sometimes it is negative. The direction matters not. The point is that such patterns have existed, and investors could have profited from that knowledge.
Whether they can still do so is doubtful. To judge from the struggles of both value and momentum investment styles, the marketplace has squeezed the juice out of those trades. As somebody once said, “if the bozos know about [the investment strategy], it doesn’t work anymore.” There are, of course, less-publicized opportunities, such as the tactics employed by some of the most successful hedge funds. We, unfortunately, are unlikely to know them.
In summary, changes in stock prices can send useful investment signals. However, except for the extremely clever, the point is moot, because by the time that the effect has been noticed and documented, its benefit has likely passed. Best, then, either to index one’s equity holdings, or if investing actively, to select stocks the old-fashioned way: by finding good businesses at the right price.
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