Do Intangibles Explain the Failure of the Value Factor?

The past decade has witnessed a dramatic increase in spending on intangibles (not just research and development and advertising expenditures but expenses related to human capital) relative to capital expenditures on plant and equipment, it should not be a surprise that researchers, including the authors of the 2020 studies, “Explaining the Recent Failure of Value Investing,” “Intangible Capital and the Value Factor: Has Your Value Definition Just Expired?” and “Equity Investing in the Age of Intangibles,” and the 2021 study “Value of Internally Generated Intangible Capital,” have focused on the impact on equity valuations and returns resulting from the change in the relative importance of intangible assets compared to physical assets.

The increasing role of intangibles is highlighted by the fact that R&D expenditures increased from 1% of company expenditures in 1975 to 7.5% in 2018 and that in 2015 services’ share of GDP stood at 74% in high-income countries and at just under 69% globally. The authors of each of the aforementioned studies found that the increasing importance of intangibles, at least for industries with high concentrations of intangible assets, is playing an important role in the cross-section of returns and thus should be addressed in portfolio construction. Not accounting for intangibles affects not just value metrics but other measures, such as profitability, which often scale by book value or total assets, both of which are affected by intangibles – and investors recognize at least some of their value.

The authors of the 2021 study, “Reports of Value’s Death May Be Greatly Exaggerated,” found that the “dark winter” (the past decade) for value stocks, during which they experienced their largest drawdown, was explained by not only a collapse in valuations of value stocks relative to growth stocks but also by the failure of the traditional HML book-value-to-price definition to capture the increasingly important intangible assets. They found that while capitalizing intangibles did not save the value premium, doing so outperformed the traditional measure by a significant margin.

Further evidence

Feifei Li, author of the paper, “Intangibles: The Missing Ingredient in Book Value,” published in the February 2022 issue of The Journal of Portfolio Management, examined the impact of adding intangibles to traditional book equity to determine if it is a more meaningful value measure. Her data sample for the U.S. covered the period July 1951-November 2019. Her international sample covered four regions (Japan, United Kingdom, Continental Europe and Asia ex-Japan) and the period July 1995-December 2019. Li divided intangible capital into knowledge capital (capitalized R&D expenditures) and organization capital (investments in advertising, brand management, expenditures on distribution systems, strategy consultants, etc.), the expenditures of which are included in reported SG&A. She used the perpetual inventory method to measure both R&D capital and organization capital, making assumptions about the depreciation rate (15% for all industries) and the level of a firm’s initial stock for both knowledge capital and organization capital. She also assumed, consistent with prior research on organization capital, that 30% of a firm’s SG&A expenditures was investment in intangible capital and the remainder was operating expense for the current period. Following is a summary of her findings:

• Mismeasurement by the traditional book-to-market metric (HML, high minus low) led to misclassification of value and growth companies and a reduced value premium.

• R&D activity was highest in the healthcare and technology sectors.

• R&D intensity increased dramatically for both the full and post-1974 sample periods between 1980 and 2000, decreased for the decade after the tech bubble burst in 2000, and rose again over the last 10 years.

• At the end of the sample period in 2018, for firms reporting R&D expenditures, the average firm spent almost 27% of annual revenue on R&D.

• When R&D capital stock is expressed as a percentage of common equity, from 1975 onward R&D capital was almost 26% of book equity for the average firm – suggesting that the standard book-equity definition understates the true book value of firms that invest in R&D.

• Adjusting the traditional value metric (book-to-market ratio) for intangibles (creating an iHML factor) improved value factor performance across subsample periods and geographic regions. The HML factor generated an average monthly return of 0.28% (t-stat = 2.9) while the iHML factor produced an average monthly return of 0.36% (t-stat = 4.3). The difference between the two is a significant (at the 5% level) 0.96% per annum.

• The outperformance of the iHML factor came from both the long and short sides of the portfolio – good news for investors under a long-only constraint. The long side of iHML outperformed by 5 basis points (bps) per month (t-stat = 2.01), and the short side underperformed by 3 bps per month (t-stat = -2.26).

• Controlling for HML, the Fama-French three-factor model (beta, size and value) and the Carhart four-factor (adding momentum) model, the alphas of the iHML factor were all positive and significant at 1% regardless of the model used. For example, iHML had a four-factor alpha of 9 bps per month (t-stat = 3.20) – using intangibles created excess returns not explained by standard factors.

• Capitalized R&D expenditures (knowledge capital) played a more important role in improving the value metric than capitalized SG&A expenditures (organization capital) – the addition of organization capital to the book value of equity did not appear to offer much performance improvement over the addition of R&D capital stock alone.

• The outperformance of value strategies, when value was defined to include intangibles, was much more pronounced among small-cap stocks (i.e., capitalization below the NYSE median). Although the alphas were also positive for large-cap stocks, they were not statistically significant.

• In the 2010-2019 subsample, although adding intangibles to book value improved the performance of value investing, investors still experienced a negative premium, demonstrated by an iHML monthly premium of -0.18% (including knowledge capital only) and -0.16% (including both knowledge and organization capital).

• International results were similar, with the iHML definition that included both R&D and organization capital stock performing better.

• In tests of robustness, the results were not particularly sensitive to the choice of depreciation rate (she also tested 10%, 20% and 25%). The results were also similar across sample periods, regions and market capitalization groups.

Her findings led Li to conclude: “Adding intangibles to the book value of equity has a positive impact on the value premium and is robust across different depreciation rate assumptions and industry-specific adjustments.” She added: “Adding intangibles to book equity to create the value measure iHML improves the value premium by about 11 bps per month, or 1.3% per year, in the United States over the sample period 1951–2019. More than half of the improvement is attributable to the long side of the portfolio. iHML also subsumes the explanatory power of traditional HML in Fama–MacBeth regressions.”

A recent study from members of the research team at Dimensional came to a different conclusion.

Conflicting findings

Savina Rizova and Namiko Saito, authors of the 2021 study, “Internally Developed Intangibles and Expected Stock Returns,” estimated the value of internally developed intangibles systematically across global markets over time by accumulating the historical spending on R&D (to capture the development of knowledge capital) and SG&A (to capture the development of organization capital) and amortizing them at fixed rates. While they too found that adding estimated internally developed intangibles would have had a slightly positive impact on the value premium over the long term and would have mitigated (but not eliminated) its underperformance in recent years, they also found that this impact was primarily driven by differences in sector weights – adjusting for sector differences largely eliminated premium differences. Their findings led them to conclude: “Our research does not find compelling evidence that we should include estimates of internally developed intangibles in company fundamentals such as book equity. The estimation of internally developed intangibles contains a lot of noise. Perhaps due to this high level of noise, we find that estimated internally developed intangibles provide little additional information about future firm cash flows beyond what is contained in current cash flows.” The result was that adjusting for internally generated intangibles did not improve upon the use of a combination of traditional value metrics plus sorting for profitability. I spoke with the AQR research team and learned that their conclusions are broadly consistent with those of Dimensional – industry-adjusting book-to-market equity captures much of what intangibles are providing in terms of excess returns.

Interestingly, Rizova and Saito also found that, “while the ratios of estimated internally developed intangibles to assets vary across sectors, they have been stable over time for each sector.” Their findings are why Dimensional’s value strategies do not attempt to adjust for internally generated intangibles. Instead, they use the traditional HML metric but also sort for profitability.

Investor takeaway

Academics and fund managers have been trying to address the issues related to intangibles not being on the balance sheet through various methods. One is to use alternatives to price-to-book (P/B) as the value metric, such as price-to-earnings (P/E), price-to-cash flow (P/CF) and enterprise value-to-earnings before interest, taxes, depreciation and amortization (EV/EBITDA). Many fund families (such as Alpha Architect, AQR, BlackRock, Bridgeway and Research Affiliates) use multiple value metrics (such as P/E, P/CF, P/S and EBITDA/EV), some of which indirectly provide exposure to the profitability factor. Another alternative is to add other factors into the definition of the eligible universe. For example, since 2013 Dimensional has included a sort for profitability in their value funds. A third alternative, as suggested by Li and others, is to add back to book value an estimate of the value of intangible R&D and organizational expenses. A fourth way to address the issue is to apply what some call “contextual” stock selection, using different metrics or different weightings of those metrics depending on the intangible intensity. For example, if book value is not well specified for industries with high intangibles, it may be less effective in those industries than in industries with low intangibles.

At any rate, at least for most practitioners, the exclusive use of the traditional HML factor to build a value portfolio is no longer standard practice. In fact, none of the fund families Buckingham Strategic Wealth uses in its portfolios exclusively use HML to construct its value funds. Stay tuned, as we are likely to see more research on this important subject.

Larry Swedroe is the chief research officer for Buckingham Strategic Wealth and Buckingham Strategic Partners.

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