[Archives] The Relation Between The Enterprise Multiple And Average Stock Returns

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New Evidence on the Relation between the Enterprise Multiple and Average Stock Returns

Forthcoming in the Journal of Financial and Quantitative Analysis

Tim Loughran

Mendoza College of Business

University of Notre Dame
Notre Dame, IN 46556-5646

(574) 631-8432 voice

[email protected]

Jay W. Wellman

School of Hotel Administration

Cornell University

Ithaca, NY 14853-6902

(607) 255-8302 voice

[email protected]

New Evidence on the Relation between the Enterprise Multiple and Average Stock Returns – Abstract

Practitioners increasingly use the enterprise multiple as a valuation measure. The enterprise multiple is (equity value + debt + preferred stock – cash)/ (EBITDA). We document that the enterprise multiple is a strong determinant of stock returns. Following Fama and French (1993) and Chen, Novy-Marx, and Zhang (2010), we create an enterprise multiple factor that generates a return premium of 5.28% per year. We interpret the enterprise multiple as a proxy for the discount rate. Firms with low enterprise multiple values appear to have higher discount rates and higher subsequent stock returns than firms with high enterprise multiple values.


In this paper, we document new evidence on the relation between the enterprise multiple (EM) and average stock returns. EM is calculated as the enterprise value (equity value + debt + preferred stock – cash) divided by operating income before depreciation (EBITDA).1 Low EM companies should be considered value firms while high enterprise multiple firms are growth firms. Our study of EM is motivated by the extensive use of EM as a valuation measure by practitioners as well as Tobin’s (1969) q-theory of investment.

Over the sample period 1963-2009, the enterprise multiple appears similar to book-to-market (BE/ME) in terms of monthly cross-sectional regression coefficients and t-statistics.

Though book-to-market and the enterprise multiple are correlated, we demonstrate that the expected return-enterprise multiple relation remains significant after controlling for book-tomarket. As book-to-market is used to create the HML factor, we use the enterprise multiple to create a factor that mimics the return differences of low-minus-high EM portfolios. The EM factor generates a premium of 0.44% per month, or 5.28% per year, significant at the 1% level.

The enterprise multiple factor remains significant after controlling for the Carhart 4- factor model (Fama-French 3-factor model plus momentum) as well as the q-theory factor model of Chen, Novy-Marx, and Zhang (2010). The alpha is 0.16% per month (t-statistic of 2.39) when using the Carhart 4-factor model and is 0.35% per month (t-statistic of 3.00) using the Chen, Novy-Marx, and Zhang (2010) market, investment, and return-on-assets factors. Since the enterprise multiple factor loads on the investment and ROA factors, the enterprise multiple is related to but not dominated by the q-theory factor model. The EM factor appears to be a more direct proxy for the discount rate and captures some of the investment and ROA factor effects.

We also examine the ability of the enterprise multiple factor to explain the value premium. Forming deciles based on alternative measures of value (book-to-market, market leverage, earnings-to-price, dividend-to-price, sales growth, and prior 36-month returns), we find the market and enterprise multiple factors can resolve the value premium puzzle when returns are value-weighted. If equally weighted returns of the value effect are the dependent variable, the enterprise multiple factor has only limited explanatory ability.

In sum, practitioner’s use of the enterprise multiple appears well justified. Low enterprise multiple firms significantly outperform high enterprise multiple firms. The enterprise multiple factor fully explains the value-weighted stock return patterns for alternative measures of the value effect and is robust to controls for the Carhart 4-factor and Chen, Novy-Marx, and Zhang q-theory models.

II. Motivation and Hypothesis Development

Our study of the enterprise multiple is motivated by its increased practitioner use as a valuation tool. Kim and Ritter (1999), in a study on IPO valuation using data from a boutique research firm, noted that while all valuation metrics had significant shortcomings, EM generally performed as well as price-to-earnings and substantially better when valuing older firms.

More recently, valuation textbooks have incorporated discussion of enterprise value and EM. The valuation textbook, “Damodaran on Valuation” (2nd edition, 2006), dedicates a full chapter to value multiples based on enterprise value. McKinsey & Company’s widely-used text, “Valuation: Measuring and Managing the Value of Companies” (4th edition, 2005), contains a detailed discussion on the use of enterprise value multiplies.

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