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  • While prior 5-year returns for the S&P 500 have been spectacular, prior 10-year returns are still muted. Does this mean the bull market still has room to run?
  • Prior returns, however, are not a great predictor of future returns.
  • Fundamentals, not returns, tend to be mean-reverting.
  • Current fundamentals are historically expensive: Shiller PE currently sits in the 89th percentile.  This implies muted forward returns over the next decade.

We read a lot of blogs. They are a great source of alternative thoughts and one way to shock ourselves out of confirmation bias.

One of our favorites is The Reformed Broker, by Josh Brown.  Josh is a pre-eminent financial personality and his blog has a tremendous amount of variety.

One of his posts this week, re: Expected Stock Returns – from the RWM Client Conference Call, caught my eye.

To quote the post,

But the number one reason investors believe returns will be muted is the fact that we’ve rallied 200% over the last 5 years. 

This reasoning is dead wrong and is symptomatic of the Gambler’s Fallacy, as in “the roulette wheel landed on black five times, so the next one just has to be red!”

But something interesting happens when you broaden out the time horizon and focus on rolling returns as opposed to calendar-year returns, which are pedestrian and meaningless in real life. We know that stock market returns are mean-reverting in the long run, even if we don’t know how far they’ll be stretched in one direction or another over the short run.


In the post he shows a graph of realized 10-year returns, which we’ve recreated here.

10-year returns sorted

The idea is that while the last 5-years have been spectacular in terms of total return, the last 10-years have been sub-par.  Since long-term returns are mean reverting, our expectation should be that the next 10 years would be better.

Except this logic is wrong for a number of reasons.

First, it invokes the very same Gambler’s Fallacy that Josh argues against.  Re-consider the first sentence I highlighted: “[b]ut the number one reason investors believe returns will be muted is the fact that we’ve rallied 200% over the last 5 years.”  Now just swap in the results over the last 10-year period and adjust some of the language: “[b]ut the number one reason investors believe returns will be better is the fact that we’ve only rallied 121% over the last 10 years.”  The logic is faulty no matter the time horizon or the order of gains and losses.

Second, the argument fails to hold up in data.  Let’s examine a scatter plot of past 10-year returns versus forward 10-year returns.

Prior 10-Year vs Forward 10-Year

If long-term returns were mean reverting, we should see a sharply negative relationship.  While a slightly negative relationship exists, the variance around it is so large that it is impossible to rely on, especially since investors only have a few decades in their investment horizon.

Finally, it has no economic merit.  Let’s ask ourselves this: why would returns be mean-reverting over the long run?  Theoretically, over the long run the market should be tied to a fundamental measure like earnings growth and the discount rate.  So if the market returns 600% over the last decade, the question we should ask is “was the growth justified?”  If it was, then why would we expect the long-term returns to mean-revert?

So how can we reconcile the slightly negative relationship we saw in the prior 10-year vs. forward 10-year scatter plot?  Surely that means there is some mean reversion?

The answer lies in the final point.  Returns are not mean-reverting, but valuations are.  Below we plot Shiller PE’s versus forward change in Shiller PE.  Notice the much, much tighter negative relationship.

Shiller PE v Change in PE

And this relationship makes economic sense: if stocks are underpriced relative to fundamentals, their valuations should increase and if stocks are overpriced, their valuations should decrease.

Now this is all complicated by the fact that fundamental metrics usually have two levers: the numerator and the denominator.  In this case, the numerator is price and the denominator is earnings.  So a high PE could revert back to a low PE because (a) price falls, (b) earnings grow, or (c) some combination of the two.  But when stocks are expensive, it doesn’t matter whether prices fall or prices sit still while earnings grow: forward returns will still be muted.

The reversion of fundamentals, therefore, has historically been a great guide for future returns – especially since prices tend to be the volatile piece of the equation.

Below we plot Shiller PE versus forward 10-year returns.

Shiller PE v Forward 10-Year Returns

So let’s go back to our slightly mean-reverting long-term returns.  Why does that happen?  The answer is that in the extremes, high valuations have coincided with strong prior returns, and low valuations have coincided with weak prior returns.

Percentile Scatter - PE v Returns

The takeaway here is that just because the prior 10-years were nothing noteworthy from a return perspective does not imply that the market necessarily has room to run.  The slight mean-reversion we saw in historical returns was a factor of coincidental data: the extremes in returns lined up with fundamental extremes.

Quite simply, prior returns are not predictive of future returns.  The fundamental data is the driver.

What we should be asking ourselves is whether we believe the market is currently cheap, expensive, or somewhere in between.  Based on the Shiller PE, fundamentals are in the 89th percentile: a fairly expensive reading.

Based on this data, we wouldn’t bet on U.S. equities being the engine of growth for the next 10 years.

Corey is co-founder and Chief Investment Officer of Newfound Research, a quantitative asset manager offering a suite of separately managed accounts and mutual funds. At Newfound, Corey is responsible for portfolio management, investment research, strategy development, and communication of the firm's views to clients.

Prior to offering asset management services, Newfound licensed research from the quantitative investment models developed by Corey. At peak, this research helped steer the tactical allocation decisions for upwards of $10bn.

Corey is a frequent speaker on industry panels and contributes to, ETF Trends, and’s Great Speculations blog. He was named a 2014 ETF All Star by

Corey holds a Master of Science in Computational Finance from Carnegie Mellon University and a Bachelor of Science in Computer Science, cum laude, from Cornell University.

You can connect with Corey on LinkedIn or Twitter.