• DocumentCode
    2485798
  • Title

    A high performance pair trading application

  • Author

    Wang, Jieren ; Rostoker, Camilo ; Wagner, Alan

  • Author_Institution
    Dept. of Math., Univ. of British Columbia, Vancouver, BC, Canada
  • fYear
    2009
  • fDate
    23-29 May 2009
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    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.
  • Keywords
    commerce; data mining; market research; marketing data processing; MPI-based infrastructure; MarketMiner; asset classes; backtesting; computational requirements; correlation measures; high frequency pair trading; high performance analytics platform; high performance pair trading; market-wide search; model formulation; real-time search; short-term correlation breakdowns; Algorithm design and analysis; Computational modeling; Computer science; Data analysis; Electric breakdown; Mathematical model; Mathematics; Open source software; Performance analysis; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel & Distributed Processing, 2009. IPDPS 2009. IEEE International Symposium on
  • Conference_Location
    Rome
  • ISSN
    1530-2075
  • Print_ISBN
    978-1-4244-3751-1
  • Electronic_ISBN
    1530-2075
  • Type

    conf

  • DOI
    10.1109/IPDPS.2009.5161147
  • Filename
    5161147