Developed by Nobel prize-winning economist James Tobin, Tobin’s Q is a financial ratio and valuation tool that can be applied either to individual businesses or to the stock market as a whole. In this article, we introduce Tobin’s Q Ratio and reflect upon some of its strengths and weaknesses.

What is Tobin’s Q Ratio?

At its most basic level, Tobin’s Q Ratio expresses the relationship between market valuation and intrinsic value. In other words, it is a means of estimating whether a given business or market is overvalued or undervalued. (For more, see: Value Investing.)

When applied to the market as a whole, we can represent this relationship as follows:

Q Ratio (Market) = Market Capitalization of all Companies ÷ Replacement Value of all Companies

If applied to an individual company, we can rephrase this relationship as:

Q Ratio (Company) = Market Capitalization ÷ Replacement Value

In either equation, a ratio greater than one would theoretically indicate that the market or company is overvalued. A ratio less than one would imply that it is undervalued.

Underlying these simple equations is an equally simple intuition regarding the relationship between price and value. In essence, Tobin’s Q Ratio asserts that a business (or a market) is worth what it costs to replace. The cost necessary to replace the business (or market) is its replacement value.

What is “Replacement Value”?

Superficially, the meaning of replacement value is clear as day. As the phrase suggests, it refers to the cost of replacing an existing asset based on current market prices. For example, the replacement value of a one-terabyte hard drive might be $50 today, even if we paid $100 for the same storage space two years ago.

In this scenario, ascertaining the replacement value would be easy because there is a robust market for hard drives from which to examine prices. To determine what a one-terabyte hard drive is worth, we would simply need to determine what it would cost to buy a one-terabyte hard drive (of comparable quality and specifications) from one of the many different suppliers on the market. In many cases, however, the replacement value of assets can prove much more elusive than this.

For instance, consider a business that owns complicated software tailor-made for its operations. Because of its highly specialized nature, there may not be any comparable alternatives available on the market. Unlike our previous example, we could not simply check to see how much similar software is selling for, because sufficiently similar software would not exist. It would therefore be difficult, if not impossible, to render an objective estimate of the software’s replacement value.

Similar circumstances present themselves in a variety of business contexts, from complex industrial machinery and obscure financial assets through to intangible assets such as goodwill. Due to the inherent difficulty of determining the replacement value of these and similar assets, many investors do not regard Tobin’s Q Ratio to be a reliable tool for valuing individual companies. (For more, see: Goodwill vs. Other Intangible Assets: What's the Difference?)

Enter the Fed

Thankfully, investors wishing to employ Tobin’s Q Ratio at the market level have a robust supply of data on which to base the market’s replacement cost. Specifically, I am referring to the data supplied in the Federal Reserve System’s Statistical Release, “Z.1 Financial Accounts of the United States.” This data, which is updated and made available on a quarterly basis, is commonly used as a proxy for the denominator of Tobin’s Q (the replacement value of all the market’s companies). (For more, see: Flow of Funds.)

Even with this wealth of data, however, there is still ambiguity regarding how precisely Tobin’s Q is to be calculated. Whether in online resources, textbooks, or academic publications, there is very little consensus regarding the finer details of how Tobin’s Q Ratio is to be calculated. Doug Short expressed one popular method in a June 2015 article for Advisor Perspectives. In it, Short uses Line 39 of section B. 103 of the Z.1 Statistical Release as the numerator for Tobin’s Q, and Line 36 of the same section as the denominator.

Yet even here, there is ambiguity regarding how this calculation is to be made. For instance, Short goes on to divide the ratio by its long-term arithmetic mean, whereas Andrew Smithers—whose work Short cites—prefers dividing the ratio by its long-term geometric mean. These kinds of difference in calculation are common among commentaries on Tobin’s Q Ratio.

The Bottom Line

Although simple in concept, applying Tobin’s Q Ratio is more difficult than it seems. Among its most notable limitations are the inherent difficulty of determining replacement value, and the inconsistency with which it is applied by practitioners. Properly investigating the various interpretations and applications of Tobin’s Q Ratio requires considerable effort and time.

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