Most of us believe that over the long run stocks are a great investment. Sure, there may be an occasional glitch – or terrifying plunge, as we’ve seen lately. But it’s commonly felt that if we just hang in there, stocks will eventually move inexorably higher.

Apparently it may be risky to have such beliefs.

Last fall I wrote about possible flaws in the ways Wall Street was assessing the riskiness of its obscure financial instruments. Now the New York Times reports there may also be flaws in the way we calculate the general riskiness of investing in stocks. After acknowledging that numerous studies of stock prices have historically found an increase in value over long periods of time, the Times notes:

But those studies were based on the stock market’s past performance, which, famously, provides no guarantee of future performance. New research, using different statistical techniques aimed at capturing the uncertainty of future returns, suggests that the market may be much riskier than many investors have understood.

This story involves a bunch of economics professors. There’s Professor Jeremy Siegel, of the Wharton School of the University of Pennsylvania and the author of “Stocks for the Long Run.” He’s an advocate of the idea that stocks increase in value over time. Then there are Lubos Pastor, a finance professor at the University of Chicago Booth School of Business, and Robert F. Stambaugh, also of the Wharton School. They argue that “uncertainty about market fluctuations increases with the holding period.”

While most people realize investing in stocks involves some uncertainty, the question is how to evaluate that risk.

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.

So why haven’t we heard about this alternative take on the risk of investing in stocks? Some might sense a conspiracy among economists and stock brokers, leading investors down a primrose path. But that ignores the fact that economists and brokers are also frequent victims of downturns in stock value.

The more likely reason is embodied in a statement commonly found in many fields: “that’s the way we’ve always done things.”

But Professor Pastor says that these methods are better suited than the standard techniques for quantifying the uncertainty faced by real-world investors. Even if Bayesian approaches have yet to become mainstream in financial research, he adds, they have become much more widely used in recent years.

One lesson we can take away from this story is to recognize that investing in stocks may be riskier than we’ve been led to believe.

But beyond that we need to realize that uncertainty is always part of our world. That’s true whether you’re a big Wall Street firm juggling obscure financial instruments or a small investor building a nest egg for retirement. All too often, the experts tend to gloss over this uncertainty, either confident in their own smarts or fatalistically resigned to the whims of chance. And all too often, ignoring uncertainty leads to disaster.

Fortunately, some experts are now devising or rediscovering ways to confront uncertainty head-on. Regardless of the field in which they’re working, it’s time we listen to what these experts have to say.