New academic paper related to #12 - Pairs Trading with Stocks Thursday, 9 July, 2015

#12 - Pairs Trading with Stocks

Authors: Goncu, Akyildrim

Title: Statistical Arbitrage with Pairs Trading



We analyse statistical arbitrage with pairs trading assuming that the spread of two assets follows a mean-reverting Ornstein-Uhlenbeck process around a long-term equilibrium level. Within this framework, we prove the existence of statistical arbitrage and derive optimality conditions for trading the spread portfolio. In the existence of uncertainty in the long-term mean and volatility of the spread, statistical arbitrage is no longer guaranteed. However, the asymptotic probability of loss can be bounded as a function of the standard error of the model parameters. The proposed framework provides a new filtering technique for identifying best pairs in the market. Empirical examples are provided for three pairs of stocks from the NYSE.

Notable quotations from the academic research paper:


"In this study, we show that pairs trading, assuming the mean-reverting spread process, satis es the de nition of statistical arbitrage. However, we also show that a time independent error in trader's guess or forecast of the long-term mean level causes the failure of the statistical arbitrage de nition. In other words, a perfect statistical arbitrage with the probability of loss decaying to zero is not available whenever there is uncertainty in the model parameters. The good news is that the probability of loss can be bounded as a function of the estimation error and given suciently good estimates, the trader can still implement pairs trading knowing the potential probability of loss involved.

Second, we derive optimal thresholds for starting the pairs trading, which can be used by the trader to select the best pairs of stocks for trade. In our framework, out of hundreds of possible pairs of assets, the trader can identify the pairs with highest probability of successful execution for a given investment horizon."

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