James Tobin, a professor at Yale University, hypothesized that the combined market value of all the companies on the stock market should be about equal to their replacement costs. Tobin developed a model to illustrate his concept, named it Tobin's Q after himself and was awarded the Nobel Prize in Economics for his trouble. Tobin's Q measurement is elegant in its simplicity, and as such has much appeal in investment circles where investors and analysts continuously seek simple means to explain complex economic and business relationships.

Tobin's Q is a perennial topic in business school curricula and occasionally turns up as a topic of investment newsletters. Yet the measure is not a common component in securities research and is not given a high profile in many of the financial services such as those provided by Bloomberg or Thomson Financial. Some fans of James Tobin, who passed away in 2002, believe that today's investors do not fully appreciate the relevance of his work, known as Portfolio Selection Theory of which the Q measure is one part.

While not meant to be exhaustive, we review here the use of Tobin's Q as a measure of valuation. We also look at the application of Tobin's Q in valuing companies in the small-cap sector.

TOBIN'S Q DEFINED

Put simply, Tobin's Q is a measure of performance comparing two valuations of the same assets. Tobin's Q is the ratio of the market value of a firm's assets as measured by the market value of its outstanding stock and debt (enterprise value) to the replacement cost of the firm's assets. If a company is worth more than its value based on what it would cost to rebuild it, then excess profits are being earned. "It is common sense," wrote Tobin, "that the incentive to make new capital investments is high when the securities giving title to their future earnings can be sold for more than the investment costs."

Tobin's Q was quickly adopted by a variety of different fields within economics, including microeconomics, finance and the study of investment. Economists took the Q measure an additional step to "Marginal Q" to illuminate the firm's investment decisions, which are made at the margin. The measure gained prominence in 1990s market boom, when researchers noted that the overall value of Tobin's Q looked unreasonably high relative to historic norms.

In their recent book Valuing Wall Street: Protecting Wealth in Turbulent Markets Andrew Smithers and Stephen Wright extended the record of the Q measure back to 1900, covering three previous secular bull market peaks. They found the value of Q at the 1960's peak (1.06) was the lowest of the three, with the highest (1.35) occurring in 1929. Thus it appears markets tend to rise significantly above one at major market peaks. The run-up from 1996 to 2000 found Tobin's Q approaching 2.0. The most recent measurement of 0.98 implies a more reasonable valuation of market conditions.

Indeed, for most of past 100 years, the ratio has been below 1.0, implying that stocks were undervalued. However, after each of the stock peaks in 1929, 1968 and 2000, the Q has crashed to around 0.4 and stayed there for a long time. Ratio bottoms (1920, 1950 and 1982) are spaced around 30 years apart.

HISTORICAL APPLICATIONS

Over the years, economists, investors and market watchers have used Tobin's Q for a variety of purposes. For investors it greatest value has likely been as a timing tool, but its usefulness in explaining industry structure or characterizing management should not be overlooked.

Market Timing Tool

In Valuing Wall Street, Smithers and Wright teach investors how to avoid losing money in the stock market by understanding and using Tobin's Q. The book explains that many times throughout history the stock market has gone through euphoric periods where stocks are extremely overvalued. By learning and applying the Q ratio, Smithers and Wright suggest an investor can measure and track the market and determine when investments are at high risk.

Viewed as a messenger of unwelcome news, Tobin's Q had fallen out of favor in the early 1990s, when calculations began suggesting that U.S. stocks were overvalued. The 2000-2002 bear market ultimately held up the validity of that call. (1) Thus we find a number of market advice columns still discussing Tobin's Q. Sharelynx Gold, at www.sharelynx.com, features a comparison of the Dow/Gold Ratio, Average U.S. House/Gold Ratio and Tobin's Q. Sharelynx Gold specializes in charts and focuses on designing and developing precious metal indices, indicators and technical analysis for evaluating the gold sector.

A variation of the market timing tool comes from market maven Jeremy Grantham, who uses Tobin's Q as a guide for long-term asset allocation. In the January 2005 issue of his quarterly newsletter entitled GMO, Grantham discusses market cycles and admonishes investors that the anticipated market low following the 2000 bubble has not net fully played out. For the short-term Grantham uses current market valuation along with the January Effect and the Presidential Cycle. For the long-term Grantham makes allocation decisions based on a slow, steady regression to the mean, which is loosely based on normalized profit margins and valuations.

Merger and Acquisitions

Analyzing mergers and acquisitions is another of the more valuable of uses for Tobin's Q. The Q model relates investment to the firm's stock market valuation, which is meant to reflect the present discounted value of expected future profits. Under certain assumptions about the firm's technology and competitive environment, the ratio of the stock market value of the firm to its replacement cost (Tobin's Q) should be a sufficient incentive for investment by the company.

Industry Research

Tobin's Q has also proven valuable in analyzing certain industries. Indeed, researchers have found a distinct relationship between Q measures and industry market structure. Market structure consists of those factors that are supposed to determine the competitiveness of an industry, affecting market performance through the conduct or behavior of firms (pricing, advertising, entry deterrence).

Firms with high Q ratios tend to have unique products and factors of production while firms with low Q ratios are typically relatively competitive or tightly regulated industries. An economist, Michael Salinger found Tobin's Q a better measure of monopoly profits than indices of single-period profitability because it measures long-run monopoly power. For example, empirical tests of the relationship between Tobin's Q and measures of market structure and unionization provide evidence that unions do capture monopoly rents in the U.S. economy. (4)

LIMITATIONS

Despite its appeal to researchers, educators and portfolio managers, Tobin's Q has detractors. Tobin's insight was based on the view that the market value of installed capital summarizes the incentive to invest. Recent research on measurement error suggests that the Q measure may not be correctly calculated if there are "bubbles" in stock market valuations that are persistent over time and that are correlated with fundamental value. (6) Although Tobin's Q is typically correlated with investment in empirical studies, researchers have found that the relationship is sometimes weak and often dominated by the direct effect of cash flow on investment. (7)

Findings for U.S. data suggest that much, if not all, of the significance of cash-flow variables in conventional estimates of Tobin's Q

Furthermore, the volatility of firms' market value greatly exceeds the volatility of the fundamentals that they supposedly summarize. Economists at Wharton School of the University of Pennsylvania and the Kellogg School of Management at Northwestern University demonstrated that models based on growth options can address this situation as well as that of cash effects. (9) They argue the presence of growth options, such as an upgrade in technology, causes fluctuation in firm valuation that are not match by current variation in cash flows.

Another major sticking point is related to measurement. For Q to be meaningful, it is necessary to accurately measure both the market value and replacement cost of a firm's assets. It is usually possible to get an accurate estimate for market value of a firm's asset by summing the values of the outstanding securities of that company. It is an entirely different task to estimate the replacement costs of those assets since the balance sheet reflects historical value not replacement value and ignores some intangibles altogether.

For example, a trio of researchers recently demonstrated that information technology (IT) assets contribute to a firm's performance potential and, if included in the calculation, have a significantly positive association with Tobin's Q value. (10) The bulk of valuation work has relied exclusively on accounting-based measure of firm performance, which largely ignore IT's contribution to performance dimensions such as strategic flexibility and intangible value. In a study that used data from 1988-1993, the inclusion of the IT expenditure variable in the Tobin's Q model significantly increased the variance explained in Q.

Researchers have developed numerous methods for computing Q, and several studies have found that choice of method can affect statistical and economic inference substantially. Although sophisticated algorithms to compute the components of Tobin's Q from accounting data can add to measurement quality, all such efforts still leave a substantial part of the variation in any proxy for Q unexplained. The measurement error problem with Tobin's Q must stem from issues such as aggregation and unobservable assets.

PRACTICAL APPLICATIONS IN THE SMALL-CAP SECTOR

In the preceding section, we cited measurement error as one of the weaknesses in Tobin's Q since it is based on accounting values that fail to acknowledge current values of historic assets or the contribution of intangibles to creating value in a company. It is reasonable to think that net worth underestimates the true value of a business, and the Q might be "reading high" in today's economy. Some make adjustments to the calculation by taking the book value of a company, adding back accumulated depreciation, and making appropriate adjustments for price changes in different classes of assets from the time of purchase. According to Michael Alexander, author of a newsletter entitled "Stock Cycles," an alternative is a valuation model based on Price to Resources (as measured by retained earnings) serves to incorporate the intangible element.

While these procedures neutralize some of the difficulties, we take the view that the weakness in Tobin's Q in its traditional form could be its strength as a valuation measure for companies in the small-cap sector.

Indeed, the small-cap company is often in an early stage of development when cash flows from the sale of its products for services have not yet materialized. Furthermore, new businesses are more likely to be based on intellectual capital as it has become the preeminent resource for creating economic wealth. (12) Tangible assets such as property, plant and equipment continue to be important factors in the production of both goods and services. However, their relative importance has decreased through time as the importance of intangible knowledge-based assets has increased. (13)

Methodologies that link intangible value to accounting measures of performance, such as return on investment, capture only tangible value components, with little consideration for intangible worth. Though these measures may have worked well for typical industrial-age companies, they don't work for new knowledge-based companies, where intellectual processes and services are the primary value drivers. Because of the substantial learning curve associated with the uses of intellectual property, such investments often take years to add value to a company and are more likely to be reflected in future profit streams. (13)

So how does an investor assess the value of such things as information systems, brand names, trade secrets, production processes, distribution channels, and work-related competencies?

We advocate turning Tobin's Q on its head and using its imperfection as the basis for analysis. Since Tobin's Q compares a company's market value to the replacement value of its physical assets, for those companies wherein the ratio of market value over book value (Tobin's Q) is significantly greater than one, the measure implies the "intangible value" in brands, reputation, knowledge or innovativeness that business analysts and shareholders are aware of and value.

The difference between market value and replacement value is the implied value of the intangibles. The next step is to evaluate whether that measure is reasonable (fair valuation) or unreasonable (overvalued or undervalued). The analyst is called to determine from what elements the intangible value arises. Is it a matter of patent ownership, brand name, or first-mover status? What are the implied cash flow streams? Is the market opportunity large enough for the company to capture the sales that would generate such cash flows? Is the company's operating structure efficient or bloated and a drain on sales? Does the company have a reasonable system to get its product to the end-user? CONCLUSION

It is clear that Tobin's Q is valuable in predicting the likelihood of market appreciation or decline, takeover activity or the rate of future capital expenditures. We also see merits for using Tobin's Q for company-specific research as a reality check on valuation in the small-cap sector, where the "irrational exuberance" cited by Federal Research Chairman Greenspan is often rampant. The analysis we advocate using Tobin's Q could be measured or simply observed. Either way, we believe the process could bring structure and integrity to the valuation of small capitalization companies.
About the Author

Debra Fiakas, CFA is a seasoned, credentialed investment professional with a diversified and successful track record as a research analyst and as an investment banker. Her decade-plus career includes solid experience in all aspects of the equity capital markets with particular emphasis on emerging growth companies operating in the technology sectors. Ms. Fiakas is also the principal member of Crystal Equity Research, LLC.