Statistical Arbitrage Trading Strategies

Some financiers believe that all information is reflected in the prices quoted for the market instruments. This is called the efficient market theory. However, whenever that market equilibrium changes--causing one or more assets to be inaccurately priced--shrewd investors utilize statistical arbitrage strategies to capitalize on this condition. In fact, many institutional traders execute trades based solely on statistical arbitrage rather than market data.

  1. Arbitrage Based On Pairs Trading

    • One type of statistical arbitrage that investors like to use is called pairs trading. This strategy hinges on the relationship between two related or unrelated equities. Also, the method is generally used in a sideways market. The equity pair is characterized by a strong statistical correlation to one another based on long-term trading histories.

      Investors wait for a five to seven percent divergence to occur which lasts for at least two to three days. At this point, the equity that lies on the bottom of the divergence is bought while simultaneously selling short the equity existing above the divergence. Whenever the pair resumes its statistical historical correlation to one another, a net profit is realized from the two trades.

    Merger and Takeover Arbitrage

    • Another form of statistical arbitrage capitalizes on takeovers and mergers. Generally, investors using this strategy will purchase stock in the target company, and then sell short the stock of the acquiring company. The profit is collected from the difference between the buyout and market prices.

      Unlike some other forms of statistical arbitrage, mergers and takeovers requires some risks. The biggest two risks involved are a possible failure of the merger settlement which causes both stocks to return to pre-merger prices, and the time value of money tied up in a merger that takes way too long to materialize.

    Volatility Arbitrage

    • Volatility arbitrage is a form of statistical arbitrage that pertains mostly to options. The strategy hinges on taking advantage of differences between the implied volatility of a particular option and that of a future forecast based on a computer model.

      Basically, whenever the implied volatility is lower than forecasts, investors look to buy options and hedge them with stocks. And if the implied volatility is higher than forecasts, the investor will sell options and then hedge them with stocks. The profits are realized whenever prices move closer to the price forecasts.

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References

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