On The Predictive Capacity of Cyclically Adjusted P/E Ratios:
This chart shows the R^2 of 10 Year Real Average Earnings, 5 Year Real Average Earnings, and the most commonly used 1 Year Real Average Earnings for the S&P 500 and how it correlates with the subsequent average S&P 500 Price. As you can see, 5 year average earnings works best and 10 year average earnings works second best for the long-term outlook. 1-year trailing earnings as a price-predictor only outperforms the CAPE during the first year.
While their is a stronger correlation between both 5 & 10 year averaged earnings and the future price of the S&P 500, the current price of the S&P 500 has a stronger correlation between the 12 month trailing earnings and price. As seen in the following chart:
We can conclude two things from this:
That the S&P 500's future average price is more correlated with metrics that look further back then a single year (such as 5 or 10 year averaged earnings).
That despite the better predictive capacity of more long-term based metrics, the overall investing community generally values the market by using single year earnings.
The central thesis therefore of utilizing the CAPE Ratio or other cyclically adjusted metrics is to capitalize on this gap in asymetrical information.
In any case, here are the predicted average future values of the S&P 500 over the next year, 3 years, 5 years, and 10 years per the current 10 Year Average Real Earnings, 5 Year Average Real Earnings, and 1 Year Average Earnings as they currently stand.
There is much more included in the excel data if you care to download it, the excel link is right here. The link is in Google Docs, it is too large for a preview so you will need to click download.
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