It’s a fraught question, dependent on various factors
including the time period tested, and the market capitalization and
industries under consideration, but I believe a consensus is
emerging.
The academic favorite remains book value-to-market
capitalization (the inverse of price-to-book value). Fama and
French maintain that it makes no difference which
“price-to-a-fundamental” is employed, but if forced to choose favor
book-to-market. In the Fama/French
Forum on Dimensional Fund Advisor’s website they give it a tepid
thumbs up despite the evidence that it’s not so great:
Data from Ken French’s website shows that sorting stocks on
E/P or CF/P data produces a bigger spread than BtM over the last 55 years.
Wouldn’t it make sense to use these other factors in addition to BtM to
distinguish value from growth stocks? EFF/KRF: A stock’s price is just the
present value of its expected future dividends, with the expected dividends
discounted with the expected stock return (roughly speaking). A higher expected
return implies a lower price.We always emphasize that different price ratios
are just different ways to scale a stock’s price with a fundamental, to extract
the information in the cross-section of stock prices about expected returns.
One fundamental (book value, earnings, or cashflow) is pretty much as good as
another for this job, and the average return spreads produced by different
ratios are similar to and, in statistical terms, indistinguishable from one
another. We like BtM because the book value in the numerator is more
stable over time than earnings or cashflow, which is important for keeping turnover
down in a value portfolio. Nevertheless, there are problems in all
accounting variables and book value is no exception, so supplementing BtM with
other ratios can in principal improve the information about expected returns.
We periodically test this proposition, so far without much success.
research seemed to say (See, for example, Roger Ibbotson’s “Decile
Portfolios of the New York Stock Exchange, 1967 – 1984,” Werner F.M.
DeBondt and Richard H. Thaler’s “Further
Evidence on Investor Overreaction and Stock Market Seasonality”). Josef
Lakonishok, Andrei Shleifer, and Robert Vishny’s Contrarian
Investment, Extrapolation and Risk, which was updated by The
Brandes Institute as Value
vs Glamour: A Global Phenomenon reopened the debate, suggesting that
price-to-earnings and price-to-cash flow might add something to price-to-book.
A number of more recent papers have moved away from
book-to-market, and towards the enterprise multiple ((equity value + debt +
preferred stock – cash)/ (EBITDA)). As far as I am aware, Tim Loughran and Jay
W. Wellman got in first with their 2009 paper “The
Enterprise Multiple Factor and the Value Premium,” which was a great
unpublished paper, but became in 2010 a slightly less great published
paper, “New
Evidence on the Relation Between the Enterprise Multiple and Average Stock
Returns,” suitable only for academics and masochists (but I repeat myself).
The abstract to the 2009 paper (missing from the 2010 paper) cuts right to the
chase:
Following the work of Fama and French (1992, 1993), there
has been wide-spread usage of book-to-market as a factor to
explain stock return patterns. In this paper, we highlight serious
flaws with the use of book-to-market and offer a replacement factor
for it. The Enterprise Multiple, calculated as (equity value + debt
value + preferred stock – cash)/ EBITDA, is better than book-to-market in
cross-sectional monthly regressions over 1963-2008. In the top three size
quintiles (accounting for about 94% of total market value), EM is a
highly significant measure of relative value, whereas book-to-market
is insignificant.
The abstract says everything you need to know:
Book-to-market is widely used (by academics), but it has serious flaws. The
enterprise multiple is more predictive over a long period (1963 to 2008), and
it’s much more predictive in big market capitalization stocks where
book-to-market is essentially useless.
What serious flaws?
The big problem with book-to-market is that so much of the
return is attributable to nano-cap stocks and “the January effect”:
Loughran (1997) examines the data used by Fama and French
(1992) and finds that the results are driven by a January seasonal and the
returns on microcap growth stocks. For the largest size quintile,
accounting for about three-quarters of total market cap, Loughran finds that
BE/ME has no significant explanatory power over 1963-1995. Furthermore,
for the top three size quintiles, accounting for about 94% of total market
cap, size and BE/ME are insignificant once January returns are removed. Fama
and French (2006) confirm Loughran’s result over the post- 1963 period. Thus,
for nearly the entire market value of largest stock market (the US) over
the most important time period (post-1963), the value premium does not
exist.
That last sentence bears repeating: For nearly the entire
market value of largest stock market (the US) over the most important time
period (post-1963),the value premium does not exist, which means
that book-to-market is not predictive in stocks other than the smallest
6 percent by market cap. What about book-to-market in the stocks in
that smallest 6 percent? It might not work there either:
Keim (1983) shows that the January effect is primarily
limited to the first trading days in January. These returns are heavily
influenced by December tax-loss selling and bid-ask bounce in low-priced stocks. Since
many fund managers are restricted in their ability to buy small stocks due to
ownership concentration restrictions and are prohibited from buying low-prices
stocks due to their speculative nature, it is unlikely that the value
premium can be exploited.
More scalable
The enterprise multiple succeeds where book-to-market fails.
In the top three size quintiles, accounting for about 94%
of total market value, EM is a highly significant measure of relative value,
whereas BE/ME is insignificant and size is only weakly significant. EM is also
highly significant after controlling for the January seasonal and removing
low-priced (<$5) stocks. Robustness checks indicate that EM is also
better to Tobin’s Q as a determinant of stock returns.
And maybe the best line in the paper:
Our results are an improvement over the existing literature
because, rather than being driven by obscure artifacts of the
data, namely the stocks in the bottom 6% of market cap and the January effect,
our results apply to virtually the entire universe of US stocks. In
other words, our results may actually be relevant to both Wall Street and
academics.
Why does the enterprise multiple work?
The enterprise multiple is a popular measure, and
for other good reasons besides its performance. First, the enterprise
multiple uses enterprise value. A stock’s enterprise
value provides more information about its true cost than its
market capitalization because it includes information about the
stock’s balance sheet, including its debt, cash and preferred stock (and in
some variations minorities and net payables-to-receivables). Such things are
significant to acquirers of the business in its entirety, which, after all, is
the way that value investors should think about each stock. Market capitalization
can be misleading. Just because a stock is cheap on a book value basis
does not mean that it’s cheap 0nce its debt load is factored into the
valuation. Loughran and Wellman, quoting Damodaran (whose recent paper I
covered here last
week), write:
Damodaran shows in an unpublished study of 550 equity
research reports that EM, along with Price/Earnings and Price/Sales, were the
most common relative valuation multiples used. He states, “In the past two
decades, this multiple (EM) has acquired a number of adherents among
analysts for a number of reasons.” The reasons Damodaran cites for EM’s
increasing popularity also point to the potential superiority of EM over
book-to-market. One reason is that EM can be compared more easily
across firms with differing leverage. We can see this when comparing
the corresponding inputs of EM and BE/ME. The numerator of EM, Enterprise
Value, can be compared to the market value of equity. EV can be viewed
as a theoretical takeover price of a firm. After a takeover, the acquirer
assumes the debt of the firm, but gains use of the firm’s cash and cash
equivalents. Including debt is important here. To take an example, in
2005, General Motors had a market cap of $17 billion, but debt of $287
billion. Using market value of equity as a measure of size, General
Motors is a mid-sized firm. Yet on the basis of Enterprise Value, GM is a huge
company. Market value of equity by itself is unlikely to fully capture
the effect GM’s debt has on its returns. More generally, it is reasonable to
think that changing firm debt levels may affect returns in a way not fully
captured by market value of equity. Bhojraj and Lee (2002) confirm this,
finding that EV is superior to market value of common equity, particularly
when firms are differentially levered.
The enterprise multiple’s ardor for cash
and abhorrence for debt matches my own, hence why I like it
so much. In practice, that tendency can be a double-edged sword. It digs
up lots of little cash boxes with a legacy business attached like an
appendix (think Daily
Journal Corporation (NASDAQ:DJCO)or Rimage Corporation (NASDAQ:RIMG)).
Such stocks tend to have limited upside. On the flip side, they also have
happily virtually no downside. In this way they are vastly
superior to the highly leveraged pigs favored by book-to-market, which
tends to serve up heavily leveraged slivers of somewhat discounted
equity, and leaves you to figure out whether it can bear the debt load. Get
it wrong and you’ll be learning the intricacies of
the bankruptcy process with nothing to show for it at the
end. When it comes time to pull the trigger, I generally find it easier to
do it with a cheap enterprise multiple than a cheap price-to-book value ratio.
The earnings variable: EBITDA
There’s a second good reason to like the enterprise
multiple: the earnings variable. EBITDA contains more information than
straight earnings, and so should give a more full view of where the accounting
profits flow:
The denominator of EM is operating income before
depreciation while net income (less dividends) flows into BE. The use of EBITDA
provides several advantages that BE lacks. Damodaran notes that differences in
depreciation methods across companies will affect net income and hence BE, but
not EBITDA. Also, the McKinsey valuation text notes that operating income is
not affected by nonoperating gains or losses. As a result, operating income
before depreciation can be viewed as a more accurate and less manipulable
measure of profitability, allowing it to be used to compare firms within as well
as across industries. Critics of EBITDA point out that it is not a substitute
for cash flow; however, EV in the numerator does account for cash.
The enterprise multiple includes debt as well as equity,
contains a clearer measure of operating profit and captures changes in cash
from period to period. The enterprise multiple is a more complete measure of
relative value than book-to-market. It also performs better:
Performance of the enterprise multiple versus
book-to-market
From CXOAdvisory:
- EM generates an annual value premium of 5.8% per year over the entire sample period (compared to 4.8% for B/M during 1926-2004).
- EM captures more premium than B/M for all five quintiles of firm size and is much less dependent on small stocks for its overall premium (see chart below).
- In the top three quintiles of firm size (accounting for about 94% of total market capitalization), EM is a highly significant measure of relative value, while B/M is not.
- EM remains highly significant after controlling for the January effect and after removing low-priced (<$5) stocks.
- EM outperforms Tobin’s q as a predictor of stock returns.
- Evidence from the UK and Japan confirms that EM is a highly significant measure of relative value.
The “value premium” is the difference in returns to a
portfolio of glamour stocks (i.e., the most expensive decile) when compared to
a portfolio of value stocks (i.e., the cheapest decile) ranked on a given price
ratio (in this case, the enterprise multiple and book-to-market). The bigger
the value premium, the better a given price ratio sorts stocks into winners and
losers. It’s a more robust test than simply measuring the performance of the
cheapest stocks. Not only do we want to limit our sins of commission
(i.e., buying losers), we want to limit our sins of omission (i.e.,
not buying winners).
Here are the value premia by market capitalization
(from CXOAdvisory again):
Ring the bell. The enterprise
multiple kicks book-to-market’s ass up and down in every weight class, but most
convincingly in the biggest stocks.
Ring the bell. The enterprise
multiple kicks book-to-market’s ass up and down in every weight class, but most
convincingly in the biggest stocks.
Strategies using the enterprise multiple
The enterprise multiple forms the basis for several
strategies. It is the price ratio limb of Joel Greenblatt’s Magic Formula (the
other limb is of course return on invested capital, which I like
about as much as Hunter S. Thompson liked Richard Nixon, about whom he
said in his
obituary:
[The] record will show that I kicked him repeatedly long
before he went down. I beat him like a mad dog with mange every time I got a
chance, and I am proud of it. He was scum.
But I digress.) It also forms the basis for the Darwin’s
Darlings strategy that I love (see Hunting
Endangered Species). The Darwin’s Darlings strategy sought to front-run the
LBO firms in the early 2000s, hence the enterprise multiple was the logical
tool, and highly effective.
Conclusion
This post was motivated by the series last week
on Aswath Damodaran’s paper ”Value Investing: Investing for Grown Ups?” in
which he asks, “If
value investing works, why do value investors underperform?” Loughran
and Wellman also asked why, if Fama and French (2006) find a value premium
(measured by book-to-market) of 4.8% per year over 1926-2004, mutual fund
managers couldn’t capture it:
Fund managers perennially underperform growth indices like
the Standard and Poor’s 500 Index and value fund managers do not outperform
growth fund managers. Either the value premium does not actually exist, or it
does not exist in a way that can be exploited by fund managers and other
investors.
Loughran and Wellman find that for nearly the entire market
value of largest stock market (the US) over the most important time period
(post-1963), the value premium does not exist, which means that book-to-market
is not predictive in stocks other than the smallest 6 percent by market cap
(and even there the returns are suspect). The enterprise multiple succeeds
where book-to-market fails. In the top three size quintiles, accounting for
about 94% of total market value, the enterprise multiple is a highly predictive
measure, while book-to-market is insignificant. The enterprise multiple also
works after controlling for the January seasonal effect and after removing low
priced (<$5) stocks. The enterprise multiple is king. Long live
the enterprise multiple.
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