What does this mean?
Well instead of starting a whole new discussion on it, the subject has been discussed in the past in this thread: PE10 predicitive [sic] power.
The thread starts with the scatter chart of 10-YR returns vs. P/E10, which shows what looks like some amount of correlation between 10-Year Return and P/E10. [I think there also used to be a 20-year return chart, but the image link is dead.]
This is followed by the astute comment that overlapping data reduces the statistical significance. It may look like hundreds of data points, but its really only about 6 independent observations for 20-year returns. Is it 13 for 10-year returns?
Another astute commenter casts doubt on the reliability of P/E10 mean reverting in your lifetime and trying to use P/E10 to forecast imminent market crashes.
But a poster makes a good point in this post that even without mean reversion, high valuations should logically lead to low returns.
But then the OP counters with "If a low PE10 predicts low earnings growth, then Gordon doesn't help the argument." and later remarks:The mean reversion refers to the change in P/E or Bogle’s speculative return. If P/E doubles or halves over 20 years, that adds or subtracts about 3.5% p.a. to returns. ... Even if P/E10 remains constant for the 20 years (no mean reversion), the Gordon equation says real returns will be higher for a lower P/E10.
But later camontgo posts a link to a 2008 paper by John Cochrane from the University of Chicago The Dog That Did Not Bark which concludes that the evidence shows that dividend growth has not been forecastable by the market. Therefore, returns must be forecastable.A low PE10 may mean we are paying less for future earnings (a bargain) or it may mean that the market is predicting low earnings and is paying a full price for them. There is no way to know ex ante.
In other words, Cochrane is saying thay high valuations forecast low returns, not high earnings and dividend growth. This would resolve the apparent dilemma in the previous quote.
Another interesting point of view is expressed in this post. The poster says:
This turns the tables. Instead of asking whether or not the data proves that P/E10 forecasts returns, the null hypothesis is:I am confident that buying stocks at lower prices and selling them at higher prices is a good investment strategy. If the statistical evidence does not reject that hypothesis, that is further proof of it, not disproof. Inconclusive statistical evidence is not sufficient to convince me that the price paid for stocks does not matter.
H0: Lower/Higher valuations lead to higher/lower returns.
Now ask if H0 should be rejected based on the data we have available.
There are a lot of other good ideas presented in that thread, although it starts to get a little technical further on. A lot more discussion about overlapping data. But the thread is worthwhile reading before starting a new discussion on valuations.
There are probably other good threads about P/E10 which have probably already hashed though everything.