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1.
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Definition
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Statistical arbitrage, or StatArb, as opposed
to (deterministic) arbitrage, is related to the statistical mis-pricing
of one or more assets based on the expected value of these assets.
For example, consider a game in which one flips a coin and collects
$1 on heads or pays $0.50 on tails. In any single flip it is
uncertain if one will win or lose money. However, in the statistical
sense, there is an expected value of $1×50% − $0.50×50% = $0.25 for
each flip. According to the law of large numbers, the mean return on
actual flips will approach this expected value as the number of
flips increases. This is precisely the way in which a gambling
casino makes a profit. In other words, statistical arbitrage
conjectures statistical mis-pricings or price relationships that are
true in expectation, in the long run when repeating a trading
strategy.
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2.
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Examples, Types, or
Variations
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As a
trading strategy, statistical arbitrage is a heavily quantitative
and computational approach to equity trading. It describes a variety
of automated trading systems which commonly make use of data mining,
statistical methods and artificial intelligence techniques. A
popular strategy is pairs trade, in which stocks are put into pairs
by fundamental or market-based similarities. When one stock in a
pair outperforms the other, the poorer performing stock is bought
long with the expectation that it will climb towards its
outperforming partner, the other is sold short. This hedges risk
from whole-market movements.
In recent years, there has been a trend away from simple
pair-trading, and now it is more common for portfolios of stocks to
be 'clustered' by sector and region in offsetting any beta exposure.
After the portfolio is constructed in this manner, it is usually
optimized using risk models like Barra/APT/EMA/Northfield to
constrain or eliminate various risk factors.
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3.
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Formula
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Attempt
to benefit from pricing inefficiencies that are identified using
mathematical models.
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4.
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Related Terms
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5.
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As
Used in the Hedge Fund World
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Statistical arbitrage has become a major force at both hedge funds
and investment banks. Many bank proprietary operations now center to
varying degrees around statistical arbitrage trading.
Other Resources:
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PICTET:
Statistical arbitrage strategies are based on the premise
that prices will return to their historical norms. These
strategies are often leveraged in order to enhance returns.
More…
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6.
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Applications
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Stat Arb
is actually any strategy that is bottom-up, beta-neutral in approach
and uses statistical/econometric techniques in order to provide
signals for execution. Signals are often generated through a
contrarian mean-reversion principle, but can also be formed by
extreme psychological barriers, corporate activity, as well as
short-term momentum. Clearly, this technique only is demonstrably
correct as the amount of trading time approaches infinity, or
alternately, it does not take into consideration what is typically
called "gambler's ruin."
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7.
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Misused & Abused
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Statistical arbitrage is subject to model weakness as well as
stock-specific risk.
The statistical relationship on which the model is based may be
spurious, or may break down due to changes in the distribution of
returns on the underlying assets. Factors which the model may not be
aware of having exposure to, could become the significant drivers of
price action in the markets, and the inverse applies also.
On a stock-specific level, there is risk of M&A activity or even
default for an individual name. Such an event would immediately end
any historical relationship assumed from empirical statistical
analysis.
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8.
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Additional Sources of Information
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Books
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News
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Scholarly Papers
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Back to Terms
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