The Q Ratio And Market Valuation: Still Overvalued

Note from dshort: Here is my monthly update with extrapolated data since the most recent Fed Z.1 report (through Q2). However, I'll post a new update on December 11th, an hour or two after the Federal Reserve's noon release of the Q3 Z.1 release.

The Q Ratio is a popular method of estimating the fair value of the stock market developed by Nobel Laureate James Tobin. It's a fairly simple concept, but laborious to calculate. The Q Ratio is the total price of the market divided by the replacement cost of all its companies. Fortunately, the government does the work of accumulating the data for the calculation. The numbers are supplied in the Federal Reserve Z.1 Financial Accounts of the United States of the United States, which is released quarterly.

The first chart shows Q Ratio from 1900 to the present. I've calculated the ratio since the latest Fed data (through 2014 Q1) based on a subjective process of extrapolating the Z.1 data itself and factoring in the monthly averages of daily closes for the Vanguard Total Market ETF (ARCA:VTI)).

Smithers & Co. (more about them later) is that "the replacement cost of company assets is overstated. This is because the long-term real return on corporate equity, according to the published data, is only 4.8%, while the long-term real return to investors is around 6.0%. Over the long-term and in equilibrium, the two must be the same."

The average (arithmetic mean) Q Ratio is about 0.68. In the chart below I've adjusted the Q Ratio to an arithmetic mean of 1 (i.e., divided the ratio data points by the average). This gives a more intuitive sense to the numbers. For example, the all-time Q Ratio high at the peak of the Tech Bubble was 1.64 — which suggests that the market price was 141% above the historic average of replacement cost. The all-time lows in 1921, 1932 and 1982 were around 0.30, which is approximately 55% below replacement cost. That's quite a range.

geometric mean for standardizing the ratio,which has the effect of weighting the numbers toward the mean. The chart below is adjusted to the geometric mean, which, based on the same data as the two charts above, is 76%. This analysis makes the Tech Bubble an even more dramatic outlier at 160% above the (geometric) mean.

Unfortunately, the Q Ratio isn't a very timely metric. The Z.1 data is over two months old when it's released, and three additional months will pass before the next release. To address this problem, I've been experimenting with estimates for the more recent months based on a combination of changes in the VTI (the Vanguard Total Market ETF) price (a surrogate for line 39) and an extrapolation of the Z.1 data itself (a surrogate for line 36).

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Based on the latest Z.1 data, the Q Ratio at the end of the second quarter of 2014 was 1.12. As of the November close, the broad market was up 5.1% (based on VTI's monthly averages of daily closes). My latest estimate would put the ratio about 73% above its arithmetic mean and 86% above its geometric mean. Of course periods of over- and under-valuation can last for many years at a time, so the Q Ratio is not a useful indicator for short-term investment timelines. This metric is more appropriate for formulating expectations for long-term market performance. As we can see in the next chart, the current level is close to the vicinity of market tops, with Tech Bubble peak as an extreme outlier.

For a quick look at the two components of the Q Ratio calculation, here is an overlay of the two since the inception of quarterly Z.1 updates in 1952. There is an obvious similarity between Line 39 and a broad market index, such as the S&P 500 or VTI. It is the more volatile of the two, but this component can be easily extrapolated for the months following the latest Fed data. The less volatile underlying Net Worth, Line 36, is not readily estimated from coincident indicators.

I added the regressions through the two data series to help illustrate the secular trend toward higher valuations.

Footnote on Z.1 Revisions: The Fed's Z.1 Financial Accounts of the United States is subject to revisions with each release. Of the two metrics used in calculating the Q-Ratio, line 36 (Net Worth) is subject to significant revisions. In Q2 2013 the data for this metric was substantially revised in light of the addition of the catch-all for intangible assets "Intellectual Property Products" to the equation. Here is the Fed's note on the change:

The effect has been a systemic lowering of the Q-Ratio.

Without the intellectual property adjustment, the Q-Ratio at the end of the second quarter of 2014 would have been 1.25 and would currently be 1.28. That would put it 79% above its arithmetic mean and 96% above its geometric mean.

The chart below shows the Q-Ratio using a calculation method shared with me a few years ago by John Mihaljevic, formerly Dr. James Tobin's research associate at Yale. It is based on several values from the Z.1 data and does not factor in intellectual property. The Q Ratio using this method of calculation is 92% above its arithmetic mean and 111% above its geometric mean.

Does it make sense to exclude intellectual property from the Q-Ratio? An email I received from a professional in the industry makes a cogent case for excluding intangible property:

One firm's competitive advantage (or intangible capital) is another's competitive disadvantage (or negative intangible capital). It is a zero sum.

Written By: Doug Short