Earlier, CNBC reported that hedge fund manager Mark Spitznagel — who runs a “black swan” fund called Universa — told clients that the odds of a market crash were increasing.
Of course, his whole fund is based on profiting from turmoil, so this is somewhat self-serving, but regardless, he’s basing his call on a market valuation model called the Q-Ratio.
What is the Q-Ratio?
Doug Short has been on top of this, tracking it, and explaining it, so we’ll use his words here:
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 Flow of Funds Accounts of the United States, which is released quarterly.
As for what you can do with the data…
The data since 1945 is a simple calculation using data from the Federal Reserve Z.1 Statistical Release, section B.102., Balance Sheet and Reconciliation Tables for Nonfinancial Corporate Business. Specifically it is the ratio of Line 35 (Market Value) divided by Line 32 (Replacement Cost). It might seem logical that fair value would be a 1:1 ratio. But that has not historically been the case. The explanation, according to 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 0.71. 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 1.82 — which suggests that the market price was 158% above the historic average of replacement cost. The all-time lows in 1921, 1932 and 1982 were around 0.30, which is about 57% below replacement cost. That’s quite a range.
And so you can see why Spitznagel sees a big crash. We’re currently 49% above the mean. And as you can see, excluding the tech bubble, this is basically the high end of the range.
Photo: Doug Short
There are other ways of massaging the data too, to get slightly different valuation readings. Read more at Dshort.com >>
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