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 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 to 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 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 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. 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.
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