Here is an combined perspective on the three market valuation indicators I routinely follow and most recently updated on Friday:

The relationship of the S&P Composite to a regression trendline (more)

The cyclical P/E ratio using the trailing 10-year earnings as the divisor (more)

The Q Ratio — the total price of the market divided by its replacement cost (more)

This post is essentially an overview and summary by way of chart overlays of the three. To facilitate comparisons, I've adjusted the Q Ratio and P/E10 to their arithmetic mean, which I represent as zero. Thus the percentages on the vertical axis show the over/undervaluation as a percent above mean value, which I'm using as a surrogate for fair value. Based on the latest S&P 500 monthly data, the index is overvalued by 65%, 45% or 40%, depending on which of the three metrics you choose.

I've plotted the S&P regression data as an area chart type rather than a line to make the comparisons a bit easier to read. It also reinforces the difference between the two line charts — both being simple ratios — and the regression series, which measures the distance from an exponential regression on a log chart.

The chart below differs from the one above in that the two valuation ratios (P/E and Q) are adjusted to their geometric mean rather than their arithmetic mean (which is what most people think of as the "average"). The geometric mean weights the central tendency of a series of numbers, thus calling attention to outliers. In my view, the first chart does a satisfactory job of illustrating these three approaches to market valuation, but I've included the geometric variant as an interesting alternative view for P/E and Q.

As I've frequently pointed out, these indicators aren't useful as short-term signals of market direction. Periods of over- and under-valuation can last for years. But they can play a role in framing longer-term expectations of investment returns. At present they suggest a cautious long-term outlook and guarded expectations.

Note: For readers unfamiliar with the S&P Composite index, see this article for some background information.

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