Statistical arbitrage : high frequency pairs trading
Abstract
In this thesis we examine the performance of a relative value strategy called Pairs Trading. Pairs Trading is one of several strategies collectively referred to as Statistical Arbitrage strategies. Candidate pairs are formed by matching stocks with similar historical price paths. The pairs, once matched, are automatically traded based on a set of trading rules. We conduct an empirical analysis using high frequency intraday data from the first quarter of 2014. Our findings indicate that the strategy is able to generate positive risk adjusted returns, even after controlling for moderate transaction costs and placing constraints on the speed of order execution.