The Returns To Value Strategies When Valuation Spreads Are Wide (Deep Value)

The academic research has generally found valuations, such as the earnings yield (E/P) (or the CAPE 10 earnings yield) and valuation spreads, have predictive value in terms of future returns. The higher the earnings yield, the higher the expected return, and the larger the spread in valuations between growth and value stocks, the larger the future value premium is likely to be in the future.(1) This relationship holds across asset classes, not just for stocks. For example, the 2007 study, “Does Predicting the Value Premium Earn Abnormal Returns?” by Jim Davis of DFA found that, despite book-to-market spreads containing information as to future returns, style-timing rules did not generate high average returns because the signals are “too noisy.” In other words, while a wider spread in valuations predicts a higher value premium, it doesn’t provide enough information to offer a profitable timing signal — allowing investors to successfully switch between value and growth strategies.

Further support that valuation spreads provide information comes from the October 2017 study, “Value Timing: Risk and Return Across Asset Classes,” authored by Fahiz M. Baba Yara, Martijn Boons and Andrea Tamoni.

The authors found the following:

Returns to value strategies in individual equities, commodities, currencies, global government bonds and stock indexes are predictable by the value spread…In all asset classes, a standard deviation increase in the value spread predicts an increase in expected value return in the same order of magnitude (or more) as the unconditional value premium.

Exploring Deep Value

AQR’s Cliff Asness, John Liew, Lasse Heje Pedersen and Ashwin Thapar contribute to the literature on the value premium with their November 2017 study, “Deep Value.” Defining “deep value” as episodes where the valuation spread between cheap and expensive securities is wide relative to its history, they examined it across global individual equities, equity index futures, currencies and global bonds. Depending on the asset class, the data sample extends as far back as 1926.