One question almost every investor asks at some point is whether
it is possible to achieve above market returns by selecting a
diversified group of stocks according to some formula, rather
than having to evaluate each stock from every angle. There are
obvious advantages to such a formulaic approach. For the
individual, the amount of time and effort spent caring for his
investments would be reduced, leaving more time for him to spend
on more enjoyable and fulfilling tasks. For the institution,
large sums of money could be deployed without having to rely
upon the investing acumen of a single talented stock picker.
Many of the proposed systems also offer the advantage of
matching the inflow of investable funds with investment
opportunities. An investor who follows no formula, and evaluates
each stock from every angle, may often find himself holding
cash. Historically, this has been a problem for some excellent
stock pickers. So, there are real advantages to favoring a
formulaic approach to investing if such an approach would yield
returns similar to the returns a complete stock by stock
analysis would yield.
Many investment writers have proposed at least one such
formulaic approach during their lifetime. The most promising
formulaic approaches have been articulated by three men:
Benjamin Graham, David Dreman, and Joel Greenblatt. As each of
these approaches appeals to logic and common sense, they are not
unique to these three men. But, these are the three names with
which these approaches are usually most closely associated; so,
there is little need to draw upon sources beyond theirs.
Benjamin Graham wrote three books of consequence: "Security
Analysis", "The Intelligent Investor", and "The Interpretation
of Financial Statements". Within each book, he hints at various
workable approaches both in stocks and bonds; however, he is
most explicit in his best known work, "The Intelligent
Investor". There, Graham discusses the purchase of shares for
less than two - thirds of their net current asset value. The
belief that this method would yield above market returns is
supported on both empirical and logical grounds. In fact, it
currently enjoys far too much support to be practicable. Public
companies rarely trade below their net current asset values.
This is unlikely to change in the future. Buyout firms,
unconventional money managers, and vulture investors now check
such excessive bouts of public pessimism by taking large or
controlling stakes in troubled companies. As a result, the
investing public is less likely to indulge its pessimism as
feverishly as it once did; for, many cheap stocks now have the
silver lining of being takeover targets. As Graham's net current
asset value method is neither workable at present, nor is likely
to prove workable in the future, we must set it aside.
David Dreman is known as a contrarian investor. In his case, it
is an appropriate label, because of his keen interest in
behavioral finance. However, in most cases the line separating
the value investor from the contrarian investor is fuzzy at
best. Dreman's contrarian investing strategies are derived from
three measures: price to earnings, price to cash flow, and price
to book value. Of these measures, the price to earnings ratio is
by far the most conspicuous. It is quoted nearly everywhere the
share price is quoted. When inverted, the price to earnings
ratio becomes the earnings yield. To put this another way, a
stock's earnings yield is "e" over "p". Dreman describes the
strategy of buying stocks trading at low prices relative to
their earnings as the low P/E approach; but, he could have just
as easily called it the high earnings yield approach. Whatever
you call it, this approach has proved effective in the past. A
diversified group of low P/E stocks has usually outperformed
both a diversified group of high P/E stocks and the market as a
whole.
This fact suggests that investors have a very hard time
quantifying the future prospects of most public companies. While
they may be able to make correct qualitative comparisons between
businesses, they have trouble assigning a price to these
qualitative differences. This does not come as a surprise to
anyone with much knowledge of human judgment (and misjudgment).
I am sure there is some technical term for this deficiency, but
I know it only as "checklist syndrome". Within any mental model,
one must both describe the variables and assign weights to these
variables. Humans tend to have little difficulty describing the
variables - that is, creating the checklist. However, they
rarely have any clue as to the weight that ought to be given to
each variable. This is why you will sometimes hear analysts say
something like: the factor that tipped the balance in favor of
online sales this holiday season was high gas prices (yes, this
is an actual paraphrase; but, I won't attribute it, because
publicly attaching such an inane argument to anyone's name is
just cruel). It is true that avoiding paying high prices at the
pump is a possible motivating factor in a shopper's decision to
make online Christmas purchases. However, it is an immaterial
factor. It is a mere pebble on the scales. This is the same kind
of thinking that places far too much value on a stock's future
earnings growth and far too little value on a stock's current
earnings.
The other two contrarian methods: the low price to cash flow
approach and the low price to book value approach work for the
same reasons. They exploit the natural human tendency to see a
false equality in the factors, and to run down a checklist. For
instance, a stock that has a triple digit price to cash flow
ratio, but is in all other respects an extraordinary business,
will be judged favorably by a checklist approach. However, if
great weight is assigned to present cash flows relative to the
stock price, the stock will be judged unfavorably. This also
illustrates the second strength of the three contrarian methods.
They heavily weight the known factors. Of course, they do not
heavily weight all known factors. They only consider three
easily quantifiable known factors. An excellent brand, a growing
industry, a superb management team, etc. may also be known
factors. However, they are not precisely quantifiable. I would
argue that while these factors may not be quantifiable they are
calculable; that is to say, while no exact value may be assigned
to them, they are useful data that ought to be considered when
evaluating an investment.
There is the possibility of a middle ground here. These three
contrarian methods may be used as a screen. Then, the investor
may apply his own active judgment to winnow the qualifying
stocks down to a final portfolio. Personally, I do not believe
this is an acceptable compromise. These three methods do not
adequately model the diversity of great investments. Therefore,
they must either exclude some of the best stocks or include too
many of the worst stocks. It is wise to place great weight upon
each of these measures; however, it is foolish disqualify any
stock because of a single criterion (which is exactly what such
a screen does).
Finally, there is Joel Greenblatt's "magic formula". This is the
most interesting formulaic approach to investing, both because
it does not subject stocks to any true/false tests and because
it is a composite of the two most important readily quantifiable
measures a stock has: earnings yield and return on capital. As
you will recall, earnings yield is simply the inverse of the P/E
ratio; so, a stock with a high earnings yield is simply a low
P/E stock. Return on capital may be thought of as the number of
pennies earned for each dollar invested in the business. The
exact formula that Greenblatt uses is described in "The Little
Book That Beats the Market". However, the formula used is rather
unimportant. Over large groups of stocks (which is what
Greenblatt suggests the magic formula be used on) any
differences between the various return on capital formulae will
not have much affect on the performance of the portfolios
constructed. Greenblatt claims his magic formula may be used in
two different ways: as an automated portfolio generation tool or
as a screen. For an investor like you (that is, one with
sufficient curiosity and commitment to frequent a site such as
this) the latter use is the more appropriate one. The magic
formula will serve you well as a screen. I would argue, however,
that you needn't limit yourself to stocks screened by the magic
formula, if you have full confidence in your judgment regarding
some other stock.
These four formulaic approaches (the three from Dreman and the
one from Greenblatt) will likely yield returns greater than or
equal to the returns you would obtain from an index fund.
Therefore, you would do better to invest in your own basket of
qualifying stocks than in the prefabricated market basket. If
you want to be a passive investor, or believe yourself incapable
of being an active investor, these formulaic approaches are your
best bet. In fact, if I were approached by an institution making
long - term investments and using only a very small percentage
of the fund for operating expenses, I would recommend an
automated process derived from these four approaches. I would
also recommend that 100% of the fund's investable assets be put
into equities, but that is a discussion for another day (in
fact, it's a discussion for Tuesday; my next podcast is devoted
to the dangers of diversification). If, however, you believe you
have what it takes to be an active investor, and that is truly
what you wish to be, then, I would suggest you do not use these
approaches for anything more than helping you generate some
useful ideas.
If you choose this path, you need to be clear about what being
an active investor entails. Read this next part very carefully
(it is correct even though it may not appear to be): I have
never found a screen that generates more than one buy order per
hundred stocks returned. Even after I have narrowed the list of
possible stocks down by a cursory review of the industry and the
business itself, I have never found a method that can
consistently generate more than one buy order per twenty - five
annual reports read. Here, I am citing my best past experiences.
In my experience, most screens result in less than one buy order
per three hundred stocks returned, and I usually read more like
fifty to a hundred annual reports per buy order at a minimum.
You may choose to invest in far more stocks than I do. Perhaps
instead of limiting yourself to your five to twelve best ideas
as I do, you might want to put money into your best twenty -
five to thirty ideas. Do the math, and you'll see that is still
quite a bit of homework. That's why remaining a passive investor
is the best bet for most people. The time and effort demanded of
the active investor is simply too taxing. They have more
important, more enjoyable things to do. If that's true for you,
the four formulaic approaches outlined above should guide you to
above market returns.
About the author:
Geoff Gannon writes a daily value investing blog and produces a
twice weekly (half hour) value investing podcast at
www.gannononinvesting.com
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