This paper describes a high-frequency pair trading strategy that exploits the power of MarketMiner, a high-performance analytics platform that enables a real-time, market-wide search for short-term correlation breakdowns across multiple markets and asset classes. The main theme of this paper is to discuss the computational requirements of model formulation and back-testing, and how a scalable solution built using a modular, MPI-based infrastructure can assist quantitative model and strategy developers by increasing the scale of their experiments or decreasing the time it takes to thoroughly test different parameters. We describe our work to date which is the design of a canonical pair trading algorithm, illustrating how fast and efficient backtesting can be performed using MarketMiner. Preliminary results are given based on a small set of stocks, parameter sets and correlation measures.
['Jieren Wang', 'Camilo Rostoker', 'Alan Wagner']
A high performance pair trading application