This paper challenges the standard method for measuring “value” used in academic work on factor pricing. This is particularly true for the high-minus-low factor (HML), which is based on the observation that companies with high book-to-market ratios (value stocks) outperform those with low ones (growth stocks).
The standard method calculates book-to-price (B/P) at portfolio formation using lagged book data, aligns price data using the same lag (ignoring recent price movements), and holds these values constant until the next rebalance. Thus by the time the data is updated the price used to determine “value” is 18 months old.
We propose two simple alternatives that use timelier price data while retaining the necessary lag for book data. We construct portfolios based on the different measures for a U.S. sample (1950–2011) and an international sample (1983–2011). We show that B/P ratios based on timelier prices better forecast true (unobservable) B/P ratios at fiscal year end.
We then show that in the context of a five-factor model including momentum, this logically superior value measure is actually superior in terms of returns. We further extend this to a monthly updated value strategy and find that, for precisely analogous reasons, the return advantage grows far stronger.
Value portfolios based on the timeliest measures earn statistically significant alphas ranging from 305 to 378 basis points per year.
The bottom line is that while the standard approach to value was a reasonable and conservative choice that has served the field well, it is not the best possible choice.
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