Price to Earnings Ratio (P/E) is a key barometer of financial conditions that gives faulty signals because both price and earnings fluctuate. The price of a stock is the subjective valuation of future corporate financial conditions. Last quarter's earnings are the financial results of business during the prior quarter and therefore trail current conditions by up to 6 months. Add inflation on top of this and the mess is hard to decipher.
The ratio of a subjective price to delayed financial earnings numbers gives some surprising results. Below is a chart of the S&P500 PE ratio with numbers taken from Robert Shiller's Irrational Exuberance Data. Notice the spike in the PE ratio during the Great Recession of 2008 which would normally indicate an overvaluation of the market. In this case it would have been the best time to enter the market in the last decade.
click to enlarge image
To be fair, the size of this spike is accentuated by the method Robert Shiller uses to report earnings. He sums the earnings over the last four quarters. This is equivalent to taking a four quarter moving average of earnings which increases the phase delay of the earnings data to about one year (2 quarters lag in reported earnings with an addition 2 quarters lag due to the moving average).
In search of a more stable barometer of economic potential, I used Robert Shiller's data from 1871 to 2012 and charted the Inflation Adjusted Total Return of the S&P500. The S&P Total Return is calculated by reinvesting the dividends each quarter and adjusting for inflation. Then, to find an average S&P500 valuation, I fit a Least Squared Linear Regression Line through the data. The average Total Return of the S&P500 can be used as a proxy for the GDP which has a long-term (more than 100 years) trend of uniform exponential growth due to changes in population and productivity. This long-term trend reflects trend line productivity growth mentioned in Ray Dalio's paper on page 4.
Even though dividend payout ratios vary greatly over time, there is a strong uniformity of the growth rate on this graph (see as a uniform liner trend on the semi-log chart). Deviation in the value of the S&P from the Least Squared Linear Regression Line indicates Bull and Bear markets cycles.
What is interesting in this chart is that the peaks and troughs of the Bull and Bear markets have striking uniformity in magnitude. The peaks of 110% in 1929 and 120% in 2000 are remarkably close in magnitude as are the troughs of 1879, 1920, 1930, 1945, and 1982. Although this is in part due to the Linear Regression process balancing equal area above and below its line, it may also indicate that the extremes of perceived valuations have had basic limits of about 110% over valuation and 55% under valuation.
Using the average value of the S&P Total Return from the linear regression, I now turn to analyze earnings relative to this stable value. With an average valuation we now have a stable denominator for analyzing the fluctuation of earnings over long periods of time. Below is a plot of S&P Earnings Yield from the average valuation of the S&P500. The long term fluctuations have been removed using a centered 20 year exponential moving average.
Notice the strong cyclical nature of the earnings yield that is not revealed by looking only at S&P500 PE. This cycle is hidden in the S&P PE because the S&P price is correlated to yield. The earnings cycle is a documented economic reality that results from businesses innovation, investment, and then competition.
At the bottom of the Great Recession of 2008 it was easy for businesses to realize earnings growth as business activity improved from depressed levels. But, as the economy normalized, it became harder and harder for businesses to improve yields. Businesses began to cut corners and squeezed the last bit of efficiency out of their workforce. Competition for customers reached a maximum as businesses over extended and over promised in the misguided anticipation of continued expansion.
We are now at what looks like a maximum in the earnings cycle. This does not mean that things are getting worse; they are just not getting better. Since the market does not like when things are not getting better, investors will slowly start to move towards the exit doors trying not to arouse suspicions that something might be amiss.