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Statistical Arbitrage          

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  1. Definition
  2. Examples, Types, or Variations
  3. Formula
  4. Related Terms
  5. As Used in the Hedge Fund World
  6. Applications
  7. Misused & Abused
  8. Additional Sources of Information
    1. Books
    2. News
    3. Scholarly Papers
       
 

1.
 

Definition
 
  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.
 

Examples, Types, or Variations
 
  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.
 

Formula
 
  Attempt to benefit from pricing inefficiencies that are identified using mathematical models.


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4.
 

Related Terms
 
 

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5.
 

As Used in the Hedge Fund World
 
 

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:

  • 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. MoreÖ


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6.
 

Applications
 
 

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.
 

Misused & Abused
 
 

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.
 

Additional Sources of Information
 
 
  1. Books
  2. News
  3. Scholarly Papers

 

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News Books Scholarly Definitions

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