COMPARISON OF OBJECT-ORIENTED PROGRAMMING AND DATA-ORIENTED DESIGN FOR IMPLEMENTING TRADING STRATEGIES BACKTESTER

Authors

  • Timur Mironov Institute of Engineering Sciences, Pskov State University
  • Lilia Motaylenko Institute of Engineering Sciences, Pskov State University
  • Dmitry Andreev Institute of Engineering Sciences, Pskov State University
  • Igor Antonov Institute of Engineering Sciences, Pskov State University
  • Mikhail Aristov Institute of Engineering Sciences, Pskov State University

DOI:

https://doi.org/10.17770/etr2021vol2.6629

Keywords:

algorithmic trading, data-oriented design (DOD), high performance computing (HPC), parallel computing

Abstract

This research proposes a way to accelerate backtesting of trading strategies using data-oriented design (DOD). The research discusses the differences between DOD and object-oriented approach (OOP), which is the most popular at the current moment. Then, the paper proposes efficient way to parallelize a backtesting using DOD. Finally, this research provides a performance comparison between DOD and OOP backtester implementations on the example of typical technical indicators. The comparison shows that use of DOD can speed up the process of quantitative features calculation up to 33% and allows for parallelization scheme that better utilizes resources in multiprocessor systems.

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Author Biography

  • Dmitry Andreev, Institute of Engineering Sciences, Pskov State University
    DMITRY A. ANDREEV. Pskov, Russian Federation. Associate Professor of the Department "Information and Communication Technologies" of Pskov State University. Lecture courses: information technologies, programming technologies, geographic information systems. Research interests: formalization of technological knowledge. E-mail: dandreev60@mail.ru

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Published

2021-06-17

How to Cite

[1]
T. Mironov, L. Motaylenko, D. Andreev, I. Antonov, and M. Aristov, “COMPARISON OF OBJECT-ORIENTED PROGRAMMING AND DATA-ORIENTED DESIGN FOR IMPLEMENTING TRADING STRATEGIES BACKTESTER”, ETR, vol. 2, pp. 124–130, Jun. 2021, doi: 10.17770/etr2021vol2.6629.