We all know that historically the stock market’s returns have made stocks one of the best investments around. Given enough time–that famous “long run”–stocks outperform almost every other asset class. There are bubbles and dips, of course, but over a course of around 30 years the market tends to revert to a mean of relatively high performance.
As professor Jeremy Siegel has shown, this pattern of mean reversion dates back to at least 1802. That’s a pretty good run. It’s a long run. But is it over? After all, this period coincides a huge boom of American economic, political and military power. We fought a Civil War, beat the Spanish Empire, fought and won two world wars, created domestic literary and artistic movements that fed a media and entertainment industry. Are we likely to repeat this performance in the future?
Yesterday’s New York Times pointed to new research that indicates that future returns of the stock market are far more uncertain than appreciated, making the market much riskier than investors believe. As investors come to grips with the study, stocks could be permanently discounted at a level below Siegel’s mean due to the additional risk.
The study was written Lubos Pastor, a finance professor at the University of Chicago, and Robert F. Stambaugh, a finance professor at Wharton. It’s title is “Are Stocks Really Less Volatile in the Long Run?”. It argues that while Siegel’s research shows that mean reversion is powerful a powerful force over long periods of time, uncertainty about market fluctuations also increases as the holding period is extended. That means, basically, that the “long run” is risky because its hard to tell what will happen in the future.
From Mark Hulbert’s column:
It is one thing to acknowledge the existence of uncertainty, but quite another to measure its influence on long-term market volatility. To do that, Professors Pastor and Stambaugh rely on a statistical approach pioneered by the Rev. Thomas Bayes, an 18th-century English mathematician. Bayesian analysis is often used to assess the uncertainty of future outcomes, based on a formula for updating the probabilities of given events in light of new evidence. This approach is quite different from traditional statistical measurements of probabilities based on historical data.
Applying Bayesian techniques, the professors found that reversion to the mean isn’t powerful enough to overcome the growing uncertainty caused by other factors as the holding period grows. Specifically, they estimated that the volatility of stock market returns at the 30-year horizon is nearly one and a half times the volatility at the one-year horizon.
There’s a bit of common sense wisdom in this. We all know that the future is hard to predict, and that it’s even harder to predict the future far off than now. For instance, most of us know our lives on Tuesday will be a lot like Monday. We’ll go to work on the same train at about the same time, eat something similar to lunch, leave work around the same time. But we would be hard pressed to predict our day 30 years from now. In the stock markets we’ve all been taught that the opposite is true: the long run is predictable while the short run is not. What if this was just another one of those economic “paradoxes” that turns out to be more myth than reality?
The upshot of this is that long term portfolios should probably be rebalanced to hold less stock, reflecting a new appreciation of the uncertainty of our future.
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