Restoring the Role of Value in Asset Pricing Models
The value eﬀect (stocks with lower valuations, as most commonly proxied by book-to-market ratio, tend to have higher returns) was one of the factors in the workhorse Fama-French three-factor (beta, size and value) and Carhart four-factor (adding momentum) asset pricing models from the early 1990s until recently.
Over the last few years, research has shown that value is redundant alongside proﬁtability and investment in explaining average returns. In other words, the value factor’s role in explaining returns is subsumed (fully explained) by its loading on the newer factors of profitability and investment.
In fact, when they were asked what they would have done differently if they knew what they do today back at the time they developed their three-factor model, professors Eugene Fama and Kenneth French concluded that in “applications where the sole interest is abnormal returns our tests suggest that a four-factor (beta, size, profitability, and investment) model that drops HML performs as well as (no better and no worse than) the five-factor model. But if one is also interested in measuring portfolio tilts toward value, profitability, and investment, the five-factor model is the choice.”
Mamdouh Medhat contributes to our understanding of the role of value in determining asset prices, and, thus, expected returns, with his June 2017 paper, “Cash and Value.” Medhat’s study focused on the role that financial policy—specifically cash—plays in asset pricing. His data sample covered the period 1962 through 2014.
Medhat called the cash factor HMS, or “hoarder minus spender.” Following practices established by Fama and French, he constructed the HMS factor by sorting ﬁrms independently into two size portfolios and three cash ratio (C/B) portfolios.
Sorts on size use NYSE medians as breakpoints, while sorts on C/B use NYSE 30th and 70th%iles as breakpoints. The portfolios are value-weighted and rebalanced annually at the end of June. Among his findings was that low-cash ﬁrms have large positive loadings on HML (meaning they are value stocks), while high-cash ﬁrms have large negative ones (meaning they are growth stocks).
This should not be a surprise, because prior research has shown value stocks are typically highly leveraged (thus providing a risk-based explanation for the value premium). Specifically, Medhat found that growth firms hold about three times as much cash as value firms, and that high-cash ﬁrms command valuations (market-to-book ratios) about 75% higher than low-cash ﬁrms—a cash strategy is a growth strategy, having implications for returns.
He then showed that, controlling for investment and profitability, both valuations and cash play important roles in asset pricing, though in opposite directions.
The explanation is that cash policy helps identify variation in valuations, with higher-cash positions indicating a higher valuation. Cash and valuations are strongly and robustly positively correlated in the cross section.
This is quite logical, as stronger cash positions should be negatively related to risk and, thus, also negatively related to forward-looking return expectations. Therefore, higher cash positions result in higher valuations, and higher valuations forecast lower returns.
That said, Medhat found that, when controlling for valuations, higher cash is associated with higher returns, and also that “controlling for cash implies considerably more power for valuations, especially in regressions that also control for proﬁtability and investment.”
Specifically, Medhat found that a combined value and cash strategy “generates a highly signiﬁcant average return of 0.57% per month with a test-statistic of 4.22. It also generates a large ﬁve-factor abnormal return of 0.30% per month with a test-statistic of 2.90.”
These findings led Medhat to conclude that cash is highly nonredundant in factor models, and that controlling for cash restores the role of value alongside proﬁtability and investment. Interestingly, Medhat also found that “without controlling for book-to-market, cash does not have power predicting returns.”
Another important finding was that, because a cash strategy is a growth strategy, it will tend do well when the value strategy performs badly. Conversely, the value strategy will tend to do well when the cash strategy performs badly.
Medhat writes: “Indeed, the time-series correlation between the monthly returns to the cash and value strategies is -0.60 with a test-statistic of -18.85.” This suggests value and cash strategies will perform extremely well in combination with each other, just as a combined value and momentum strategy works well.
For Medhat, the important implication of his findings is that “failing to account for cash detrimentally conﬂates value with the proﬁtability and investment eﬀects. In other words, while it is true that value ﬁrms do not outperform growth ﬁrms with similar proﬁtability and investment, they do, in fact, signiﬁcantly outperform growth ﬁrms with similar proﬁtability, investment, and cash.”
I think it will be interesting to see whether fund families begin to incorporate Medhat’s findings into fund construction methodologies.
This commentary originally appeared November 15 on ETF.com
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