Recent research shows that B/M is losing explanatory power (Asness et al. 2015, Fama-French 2015, Hou et al. 2015). Some have theorized that the decrease in effectiveness in B/M is due to the increasingly large value of intangible assets. Forty years ago the market was dominated by Kodak, General Electric, and Xerox all companies with huge manufacturing businesses with book values built on piles of assets to make film, jet engines, or copy machines. Today’s market is dominated by a different type of company with almost no manufacturing capacity Microsoft, Google, or Apple, where the book value isn’t as accurately reflecting the underlying value of the business.
This paper asks the following question:
Does an “adjusted” (intangibles-based) book value of a company on its balance sheet provide value-relevant information for investors?
What are the Academic Insights?
The categories of intangible assets include 1) marketing-related, 2) customer-related, 3) contractrelated, 4) technology-related, and 5) other unspecified intangible assets.
After estimating unrecorded intangibles, the author adjusts the book values of firms using the estimates to calculate the intangible-adjusted B/M ratio (iB/M), which is based on two adjustments for book values: capitalizing unrecorded knowledge capital (Kcap) and organization capital (Ocap) and subtracting goodwill that is subject to the issue of unverifiable fair value estimates and finds:
YES, iB/M outperforms B/M in Fama-MacBeth (1973) regressions to explain future stock returns after controlling for the differences in size, profitability, momentum, and short-term reversal. The iB/M coefficient is larger and more significantly different from zero than that of B/M in both large and small stocks
YES, portfolio-level tests confirm the superior performance of iB/M. The excess return of the high minus low iB/M decile portfolio constructed as in Fama and French (1992) is larger and more significantly different from zero than that of B/M. When the excess returns are regressed on the market, size, profitability, and investment factors as in Fama and French (2015 and 2016), the alpha of the iB/M portfolio is positive and significantly different from zero while the B/M alpha is not significant
When high-minus-low (HML) portfolios are formed as in Fama and French (1993 and 2015), iHML outperforms HML significantly
When comparing iB/M with other variations based on retained earnings, tangible book value, goodwill inclusion, knowledge capital, and organization capital, and find that iB/M is the best alternative to B/M
iHML still explains average US stock returns for 1976 – 2017 while HML does not. This finding is consistent with Fama and French (2015) who show that HML is redundant for explaining average US stock returns from 1963-2013.
Why does it matter?
The B/M measure has been widely used in asset pricing studies since the seminal research of Fama and French (1992 and 1993), and value funds are using the measure for stock valuation and index construction despite growing evidence in the literature showing that the B/M measure is losing explanatory power in the cross-section of stock returns. This study argues that the growth of goodwill and unrecorded intangible assets are related to the change and proposes an updated version that includes intangibles and works well in explaining the cross-section.
The Most Important Chart from the Paper:
The book-to-market ratio has been widely used to explain the cross-sectional variation in stock returns, but the explanatory power is weaker in recent decades than in the 1970s. I argue that the deterioration is related to the growth of intangible assets unrecorded on balance sheets. An intangible-adjusted ratio, capitalizing prior expenditures to develop intangible assets internally and excluding goodwill, outperforms the original ratio significantly. The average annual return on the intangible-adjusted highminus-low (iHML) portfolio is 5.9% from July 1976 to December 2017 and 6.2% from July 1997 to December 2017, vs. 3.9% and 3.6% for an equivalent HML portfolio
Dr. Elisabetta Basilico is a seasoned investment professional with an expertise in "turning academic insights into investment strategies." Research is her life's work and by combing her scientific grounding in quantitative investment management with a pragmatic approach to business challenges, she’s helped several institutional investors achieve stable returns from their global wealth portfolios. Her expertise spans from asset allocation to active quantitative investment strategies. Holder of the Charter Financial Analyst since 2007 and a PhD from the University of St. Gallen in Switzerland, she has experience in teaching and research at various international universities and co-author of articles published in peer-reviewed journals. She and co-author Tommi Johnsen published a book on research-backed investment ideas, titled Smarte(er) Investing. How Academic Insights Propel the Savvy Investor. You can find additional information at Academic Insights on Investing.
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