The Value Imperative -- Part 2: Replacement Value and Tobin’s q theory
If you are considering trading in your car, as a value investor how do you evaluate the different possibilities? Do you value your existing car in terms of what it would cost to replace it rather than its price in the Kelley Blue Book? If so, you may be following in the steps of Nobel laureate James Tobin who studied the relationship between fair value and replacement cost.
In the first article in this series I introduced the notion of value and some of the main issues in understanding and measuring it. In this article I introduce the notion of the q-ratio as the first of a number of ways that value can be measured.
The q-ratio was introduced by James Tobin in 1969 and measures the relationship between fair value and replacement costs. In the words of Tobin, q is
the ratio between two valuations of the same physical asset. One, the numerator, is the market valuation: the going price in the market for exchanging physical assets. The other, the denominator, is the replacement or reproduction cost: the price in the market for newly produced commodities. (Asset Markets and the Cost of Capital, James Tobin and William Brainard, Cowles Foundation, 1976)
As with so much in economics, this idea was first stated by John Maynard Keynes. In 1936 in The General Theory of Employment, Interest and Money he wrote:
[The] daily revaluations of the Stock Exchange, though they are primarily made to facilitate transfers of old investments between one individual and another, inevitably exert a decisive influence on the rate of current investment. For there is no sense in building up a new enterprise at a cost greater than that at which a similar existing enterprise can be purchased; whilst there is an inducement to spend on a new project what may seem an extravagant sum, if it can be floated off on the Stock Exchange at an immediate profit.
It seems fairly intuitive that q should not stray too far from a value of 1 and if it does, market forces will conspire to bring it back. Suppose the market capitalization of a business that produces widgets greatly exceeds the establishment of a new widget business. Enterprising financiers will keep building widget companies and floating them on the market at a substantial profit until the world has a glut of widgets.
On the other side, if the market price was substantially lower than the cost to build a new widget company, no one would build any new companies that produced widgets. The profitability—and the stock prices—of the existing businesses would rise. Eventually the profits would justify the construction of new widget businesses.
Despite the intuitive appeal that q should hover around 1 and before we look at the fact of whether or not it is true in practice, there are various consequences that most people find quite surprising. Here are a few examples:
1) The fair value of a business is independent of short and long term interest rates. Why? Since interest rates do not affect the replacement costs of businesses, the same must apply to their fair value in the market. This contrasts to the so-called Fed Model that the yield on the 10-year U.S. Treasury Bonds should be similar to the S&P 500 earnings yield with the conclusion that the market moves in the opposite direction to the bond rate.
2) Tax changes such as capital gains tax rates are irrelevant to replacement cost and hence play no part in fair market value.
3) Inflation is a pass-through variable and does not affect the real replacement value and hence the fair value remains untouched by inflation levels.
As governments know when they twiddle with interest rates, markets do rise with falling interest rates and low inflation, and vice versa. From the perspective of q-theory, however, this is a behavioral response. When rates and inflation are low, investors look around for higher returns and so are willing to pay more for stocks.
There are various issues with q. The first is that there a number of competing definitions. Also it does not apply to all companies. For example, financial institutions are usually not examined using q. Also, there are questions about its suitability to businesses with considerable land assets.
The second issue is that there is debate about its applicability to individual companies. Andrew Smithers is very clear in his opinion that q does not apply to individual companies. “This is mainly because the impact of intangibles is very different,” he wrote in Valuing Wall Street: Protecting Wealth in Turbulent Markets. "Whilst these don’t affect the aggregate value, they can be very important for individual companies.”
On the other hand, the asset management firm GMO makes systematic use of it in allocating capital and selecting companies for their portfolios which total over $150 billion.
The following chart shows the strong mean-reversion quality of the q-ratio over the period 1900 to 2006.
The chart shows q relative to its long-term average in logarithmic terms. When it is at zero, according to q-theory the US stock market is at fair value; when it is negative, the market is cheap, and vice versa. A score of 1 in logarithmic terms represents a score of 2.7 in non-logarithmic terms. In 2000, the market was overvalued by 2.7 times its normal valuation.
A proxy to q is the cyclically adjusted PE ratio for the market as introduced by Robert Shiller. This is calculated as the price divided by the average earnings per share over the previous 10 years. The following chart shows just how strongly they track each other.
The charts show that as we moved towards the end of 2006 the market valuation was decreasing rapidly from its high at 2000. Even so, at the end of the year it was still overvalued. With the recent market correction, it will be interesting to see if it has dropped to its fair value. Stay tuned!
In the third article in this series I am going to move right away from Nobel-prize winning finance and economics and look at charting and technical analysis. Does it really work? Can it uncover value in the stock market? I will look at a recent study by David Aronson examining 6,402 technical analysis rules on the S&P 500 over almost 15 years involving such things as moving averages, channel breakouts and stochastics. I'll let you guess what percentage of these rules showed a statistically significant profit.
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