Every profession has its buzzwords to create the illusion that
things are more complex than they really are. Everything from the
Latinterms used by medical doctors to the chatter of gearheads
talking about the latest car engine, simple concepts are often
clothed in complicated-sounding terms.
Investing professionals are no different in their use of
complicated nomenclature to describe simple things and
I know I was intimidated when I first heard theterm
statisticalarbitrage . To me, it sounded like I would need a math
Ph.D. or at least an advanced understanding of statistical theory
to figure out what it meant. Not being an advanced math person, I
was fortunate to have had a trading mentor who patiently
explained to me what statistical arbitrage is and how to use it
Ever since I was made aware of this unique and profitable
trading technique, I have used it in a variety ofmarket
conditions to capture profits that would otherwise be
unavailable. This method's not for everyone, but if you're an
active investor who is looking for additional tricks of the
trade, statistical arbitrage may be just the ticket.
What Is Statistical Arbitrage?
Simplyput , statistical arbitrage is a fancy term for pair
trading, which is the buying or selling of a pair ofstocks based
on their relationship with each other.
Often, thestock price of companies in the same sector or type
of business follows one another very closely. A pair trader
observes the relationship between two stocks and buys or sells
whenever the relationship gets out of sync, acting on the
assumption that the historical correlation is likely to
Is it a foolproof method? No, but it does provide another
tactic in your investing toolbox.
It is easier to understand this concept with an illustration.
The following chart shows the relationship between
, perhaps the most popular stock pair for statistical
Notice how closely the two stocks follow each other until near
the end of May. At this time, Pepsico falls out of sync with
Coca-Cola, dropping as Coca-Cola stays steady and starts to
climb. Statistical arbitrage traders would purchase Pepsico stock
as soon as the divergence is recognized.
As you can see, the pair quickly moved back into sync,
providing aprofit opportunity for statistical arbitrage traders.
There aremultiple ways this can be approached.
For example, let's say Coca-Cola started rapidly climbing
higher than Pepsico. Savvy statistical arbitrage traders would
short Coca-Colashares in anticipation of its price falling back
into the historic correlation.
In addition, the idea is not just limited to two stocks. The
same idea can be applied to groups of three or more correlated
names. However, special software is often employed to manage
multiple-issue statistical arbitrage.
Here's another well-known pair trade:
As you can see, Target climbed out of the historical
correlation range on the chart. Traders invested in the pair
would short Target, holding until the historical correlation came
back into sync.
It's important to remember that it's not always obvious names
that present enough correlation to pair-trade. One example of
this is the relationship between
Other than trading on the same exchange, I cannot imagine why
two companies that are so diverse would be correlated so closely.
The reason could have something to do with the fact that
consumers may borrowmoney to buy Harley-Davidson motorcycles, but
that's only a guess.
Risks to Consider:
Although closely correlated stock pairs generally come back
into sync with each other after diverging, there is no rule that
says this has to happen. Stock pairs can stay out of sync for a
substantial period of time, depending on the underlying
circumstances. Always use stops and position size properly.
Action to Take -->
Begin to chart the common pairs like Coca Cola and Pepsico,
General Motors (GM)
, and other closely related companies. In addition, experiment
with finding correlated pairs by simply charting a variety of
pairs of stocks. Although I like to use daily charts, tradable
correlations can be found in all timeframes. Professional traders
often use software, rather than visual charts, to find historical
pairs showing a statistical aberration from each other. Some
trading platforms have this ability built in, but this type of
software is readily available.