Risk
Defined, Generally
The
Merriam-Webster dictionary defines risk as "the
possibility of loss or injury." This definition
is natural to most people; the average individual associates
risk with some manner of negative outcome. But
the negative connotation is in many ways counterproductive
because every activity, every decision, carries with it
some degree of risk. As human beings, our success
as a species is in part due to our aversion to risk. But
our instincts for survival have also resulted in us being
quite poor at objectively evaluating risk and calculating
the probabilities of events. Our emotions often
work against us, and many of the mathematical and statistical
tools we have developed for appraising probabilities
and risk have made us worse at the task, not better -
at least where investing is often concerned.
Risk
vs. Uncertainty
Although
it's a subtle difference, there is more than a semantic
difference between uncertainty and risk. Seeing
the two as distinct is not intuitive, but understanding
how they differ and perhaps overlap is an important aspect
of risk analysis. The difference might best be
explained through example:
Uncertainty is
what meteorologists grapple with in trying to forecast
the weather.
Risk is
what the gambler confronts in placing bets on a roulette
wheel.
Meteorologists
have yet to construct a model that consistently and accurately
forecasts the weather because there are simply so many
possible outcomes. In addition to the almost limitless
list of outcomes, the weather has so many inputs and
influences that scientists have yet to produce a model
capable of translating them into reliable forecasts.
By
comparison, roulette has a defined set of possible
outcomes - an American roulette wheel contains 38
numbers, and the ball has to land on one of them.
Predicting
the weather is the realm of uncertainty because of the
superabundance of inputs and outcomes. Were there
not nearly so many factors influencing the weather, forecasting
might be more a function of risk than uncertainty. In
that sense, one can see how risk takes on the unpredictability
of uncertainty when the totality of inputs and outcomes
becomes so complex that predicting a single outcome with
certainty is functionally impossible. Having certainty
as to a specific outcome means that the subject outcome
has a high probability of occurring. This is the
interactive relationship between certainty, risk and
probability.
Investment
Risk Defined, Incorrectly and Correctly
Most
professional investment managers define risk as volatility
in price, and they measure that volatility utilizing
standard deviation (if you are unfamiliar with standard
deviation, variance, and other statistical measures,
please see
Primer on the
Misapplication of Statistical Analysis to Investing,
which discusses these issues in much more detailed and technical
terms). As Harry Markowitz, one of the intellectual
founders of Modern Portfolio Theory (MPT), set out in his
1959 text Portfolio Selection: Efficient Diversification
of Investment, "I use standard deviation as a
measure of risk."
Standard
deviation, as well as variance (a related statistic),
indicate risk by measuring the volatility in security prices
in terms of how widely dispersed those prices are. The
more a price bounces away from its average, the more it's
deviating or varying from the average, and hence the more
volatile. It's this volatility that's taken under
MPT to be a reliable indicator of the amount of risk in
the investment.
Thus,
under Modern Portfolio Theory, risk is ultimately defined
by volatility in security price:
Standard
Deviation of Security Price = Volatility
of Security Price
Volatility
of Security Price = Risk of Security
This
is misleading and incorrect.
Some
of the "smartest" minds in investing would of
course vehemently disagree with me. And I quote:
"Risk
is a function of volatility. These things are quantifiable."
The
preceding quote was by Peter Rosenthal, press spokesman
for Long Term Capital Management. If you're not familiar,
Long Term Capital was an investment partnership that was
thought to comprise the keenest intellects in the investment
world, including two Nobel Prize-winning economists. It
imploded in 1998, and were it not for the intervention
of fourteen banks that committed a total of $3.65 bil.
in capital, it might have taken a great part of the US
financial markets with it.1
Consider
the following example (it's an extremely simple one, but
it makes the point):
There's
a company, "X," whose shares are trading at $50. Early
one morning, a rumor circulates that this company is bankrupt. There's
no basis for this, but the shares drop to $25 on the "news." Let's
say the company was actually a fairly attractive buy at
$50. Because it is now trading at $25, a 50% discount
to the prior day and with no actual change in the financial
aspects or economics of its underlying business, according
to MPT this company has actually become riskier because
it has become cheaper.
But if
the same assets can be purchased for half of what they
would have cost the day before, that investment isn't more risky
- it's less risky because the lower price
affords an even greater margin of safety.
Price
volatility has nothing to do with risk. There is
a much more intelligent, more logical definition:
Risk
= The Possibility of Financial Harm
"The
possibility of financial harm" doesn't mean that the
price of the stock drops, but rather that the prospective
returns on the investment drop. (For more information
on calculating future returns, consult the Valuation section
of this website; more broadly, value is addressed in the Philosophy section.)
Imagine
now that the total market capitalization for company X
is $100 mil. if the shares are trading at $50. Assume
that X generates $10 million in net income, which under
the circumstances is attractive. At $100 mil. market
cap, that $10 million X generates translates into a 10%
net margin.
When
the price of the entire company, which in this case is
the market capitalization (X has no debt, so one can purchase
all claims on the business by simply purchasing all of
the outstanding shares), drops to $50 mil. because the
price of the shares has dropped by 50% from $50 to $25,
that means that X is now generating 20% net margins ($10
mil. divided by $50 mil.).
The
question is:
If
X is still generating that $10 mil. in net income year
in and year out, how has the risk increased because
the stock price has dropped? And doesn't the level
of risk decline if one purchases more shares of the same
business at lower prices?
Risk
is about the likelihood of the intrinsic value of the
business declining,
not the
price behavior of the stock.
If
I owned 100% of Company X, would I care if one day someone
walked in the door and offered me $50 mil. for a business
that was worth $100 mil. to me? I'd ignore him -
and this should still be the case even if one owns 1% of
the company, or even less.
Forget
about the price; focus on the business.
In
1963, American Express plummeted from $65 per share to
$35 in a matter of days. At that point running his
first partnership, Warren Buffet proceeded to put 40% of
the partnership's total assets into Amex. The shares
tripled in price in 2 years, and he made a fortune on that
position alone. He didn't care about the volatility,
which had gone through the roof, and he didn't care about
his concentration, because he knew great investment opportunities
don't come along that often. The key is to bet big
when they do, and when he looked closely and saw an attractive
business at Amex, that's exactly what he did.
Portfolio
Diversification and Concentration
Owning
a concentrated portfolio with fewer companies is defensive, not more risky.
Wide
diversification is, generally speaking, little more than
a crutch against ignorance. Why in the world, after
weeks of searching for a company that's worth owning for
the long haul, would one want to diminish the impact of
owning that truly great company by surrounding it with
a bunch of mediocre ones? Or by only owning a minute
position in it?
Position
size is indeed critical - the data confirm this. In You
Can Be a Stock Market Genius, Joel Greenblatt offers
the following statistics:
-
Owning two
stocks eliminates 46% of non-market risk of just
owning one stock
-
Four stocks
eliminates 72% of the risk
-
Eight stocks
eliminates 81% of the risk
-
16
stocks eliminates 93% of the risk
-
32
stocks eliminates 96% of the risk
-
500
stocks eliminates 99% of the risk
This
confirms that diversification beyond perhaps 10 stocks
does little to reduce risk. Beyond approximately
a dozen stocks, diversification only serves to diminish
returns.
For
the investor who limits herself to only the most outstanding
opportunities, the above is ultimately irrelevant - there
are only a handful of truly worthwhile investments that
can one discover in the space of a year anyway. Even
the best investors in the world only come up with a handful
of good ideas in a year. And they always bet big
when they do.
Bet
big when the odds are with you, and not at all when
they're not.
The
shrewdest investors have embraced the fact that they can
only have in-depth, detailed knowledge of a very small
number of situations.
Knowledge is
what insulates us from risk;
knowledge
decreases with diversification, but risk decreases
with increasing knowledge.
The
reality of the "business" of investing (vs. investing
solely in order to produce the highest returns possible)
is that very few money managers get fired by owning a stock
that is well known and considered "solid" by
the financial press. If a mutual fund manager loses
money because he bought IBM stock, well, IBM is a great
company - everybody knows that, right? IBM
will come back. This is what they said about the "nifty
fifty" stocks like Polaroid. Taken a look at
Polaroid lately?
Conversely,
if the same manager buys Widgets Inc. and the stock drops
in price, even if he knows the company inside out and it's
a great company, he's dismissed as foolish. A year
later, when Widgets Inc. fulfills its potential and trades
up 140%, he won't be there because he'll have been fired
for buying something that nobody had heard of that went
down in price. This is why 90% of mutual funds not
only fail to match the performance of the S&P,
but dramatically underperform the index. Better to
be a live lemming than a dead oracle. This is the
conclusion most fund managers come to, consciously or otherwise. They're
in business to be in business. Call it The
Institutional Imperative. Or simply survival. But
regardless of what you call it, it's diametrically opposed
to investors' interests.
Caveats
and Criticisms
The
chief criticism leveled at the above approach is that it
can only work if the investor not only has superb judgment, but also
an extremely detailed knowledge of their investment,
neither of which is apparently achievable. Thus, the investor
is ultimately advised to give up before they start; you
can't know, so don't try.
Given
how little research most analysts and portfolio managers
actually do on their investments, the above viewpoint is
ironic - because the pros don't do the work, others are
incapable of doing it? But individuals should give
their money to them anyway because they're
the professionals and they know what they're doing? What?
Defining
when one has an authentically thorough grasp of a company's
fundamentals is an admittedly slippery practice. Because
every company is different, what constitutes
a complete analysis can be a moving target. As for
what it means to achieve that level of knowledge, in addition
to my general comments in the Philosophy page,
in the Investment Analysis page
I offer some explicit criteria that I personally find very
practical in maintaining an objective viewpoint on the
diligence of my own process.
1
When
Genius Failed, Roger Lowenstein, p.64.
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