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Dimensional's Marlena Lee: How to Measure Value

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When Marlena Lee speaks, members of IFA's investment committee like to listen. As head of the global investment solutions group at Dimensional Fund Advisors (DFA), her analysis over the years has covered major investment questions surrounding issues related to market pricing, factor performance and asset-class diversification, among others. In this question-and-answer session, we discuss how Dimensional quantifies and utilizes long-term premiums to gain from tilting fund portfolios to value-styled stocks. 

IFA: Is there a value premium?

Marlena Lee: Yes. There are many reasons one should expect differences in expected returns among securities.

IFA: How might investors identify those differences?

Marlena Lee: Valuation theory provides us with a framework about the drivers of expected stock returns. It tells us that a stock's current market value reflects information about future cash flows discounted by the expected stock return. Therefore, we can use price variables, such as market capitalization and relative price, combined with cash flow variables like profitability to identify reliable differences in expected stock returns. 

While it is a theoretical approximation, this framework provides us with a few important relations between company characteristics and expected stock returns.

One insight is that, all other things being equal, the lower the price paid for a security (measured by market capitalization or relative price), the higher the expected return.

Another insight is that (for a given price), the higher the expected future cash flows to shareholders, the higher the expected return. Current profitability has information about future profitability. Past investment -- for example, asset growth over the prior year -- has information about future investment. Future profitability and future asset growth have information about future cash flows.

Taking these together, we infer that, all else equal, stocks with smaller market capitalizations, lower price-to-book ratios, higher profitability and lower investment have higher expected returns. 

IFA: A wealth of academic research supports a global view of these factors driving long-term returns, doesn't it?

Marlena Lee: There are numerous academic studies documenting the existence of those premiums covering over 40 countries and nine decades of stock data. Those studies have also shown that realized premiums are volatile, which implies that there is a 'non-zero' probability that realized premiums can be negative over any investment horizon, even if in expectations they are positive every day.

That probability decreases the longer the horizon, but it never goes to zero. For instance, our research shows that, for the value premium, the probability of a 'negative' value premium decreases from 40% at one year to 17% at 10 years. (Note: See an explanation of how probability is computed in this case at the end.) 

IFA: How do you measure it? 

Marlena Lee: While book value is a fundamental accounting variable that has been frequently used to scale a stock's price to document the value premium, there have been many variables used: price-to-earnings, price-to-cashflows and price-to-sales that also show a similar return pattern. That is, the value premium is robust to the variable used to scale price.

The important common element across these studies is not the fundamental variable used, it is that the studies use market price.

From an investor's perspective, however, the choice of scaling variables does matter because different variables could have a different impact on portfolio diversification or turnover -- or, interact with other premiums in different ways. For instance: earnings, cash flow and sales all scaled by price (or a blend of those metrics) do not contain additional information about expected returns beyond the information contained in market capitalization, profitability and price-to-book.

This suggests that using multiple metrics to measure the value premium may add complexity to an investment process without improving our understanding of differences in expected returns among securities. And that price-to-book ratios remain a useful variable to identify value premiums.

IFA: How do you know that P/B continues to be relevant?

Marlena Lee: We run an ongoing test to see how the relation between price-to-book and subsequent returns has evolved over time. The test examines five-year rolling averages of the absolute value of t-statistics from cross-sectional regressions of stock returns on lagged price-to-book.

T-statistics from these regressions have not shown any downward trend in the informational content of price-to-book about the cross-section of returns. In other words, price-to-book still has information about cross-sectional dispersion in returns. If price-to-book were no longer relevant, we should expect to see a decline in its ability to produce spreads in returns.

One characteristic that many investors cite as a concern with using price-to-book is intangible assets. Dimensional has conducted extensive research on different metrics for measuring value versus growth, including adjustments to reflect intangibles (e.g., trademarks, copyrights, patents, franchises, computer software, reputation and brand name). We do not find adjustments for intangibles to have a big impact on the magnitude of the value premium.

Under current accounting practices, externally acquired intangibles are reported on the balance sheet. For example, they currently represent about a quarter of the book value of assets for the average US company. We account for these assets when computing book values. Internally developed intangibles, on the other hand, are expensed and thus reflected on the income statement. 

We have conducted research to estimate internal intangibles for publicly traded companies over time. The data suggest that there have not been meaningful trends in these intangibles over the past number of decades for the overall market. 

Moreover, we observe strong premiums sector by sector when sorting stocks on price-to-book—including sectors that tend to involve more intangible assets such as technology and healthcare.


Probability of outperformance is computed using percentage of rolling 1- and 10-year periods with a negative value premium is calculated using monthly return data from June 1927 to December 2019. Value is defined as Fama/French US Value Research Index minus the Fama/French US Growth Research Index. Past performance is no guarantee of future results. Indices are not available for direct investment; therefore, their performance does not reflect the expenses associated with the management of an actual portfolio. Fama/French indices provided by Ken French. Eugene Fama and Ken French are members of the Board of Directors of the general partner of, and provide consulting services to, Dimensional Fund Advisors LP.


The "t-stat" tests whether or not a given sample mean is statistically different from zero. See t-stat in glossary.

This is not to be construed as an offer, solicitation, recommendation, or endorsement of any particular security, product or service. There is no guarantee investment strategies will be successful. Investing involves risks, including possible loss of principal. Performance may contain both live and back-tested data. Data is provided for illustrative purposes only, it does not represent actual performance of any client portfolio or account and it should not be interpreted as an indication of such performance. IFA Index Portfolios are recommended based on time horizon and risk tolerance.  For more information about Index Fund Advisors, Inc, please review our brochure at https://www.adviserinfo.sec.gov/ or visit www.ifa.com.