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Numerical methods and programming, 2012, Volume 13, Issue 1, Pages 28–32 (Mi vmp4)  

Вычислительные методы и приложения

Optimization of trading strategies by parallel evolutionary computation on graphics processing units

O. G. Monakhov

Institute of Computational Mathematics and Mathematical Geophysics (Computing Center), Siberian Branch of the Russian Academy of Sciences, Novosibirsk
Abstract: An approach to the optimization of trading strategies (algorithms) based on indicators of financial markets and evolutionary computation is described. A parallel version of a genetic algorithm for searching optimal parameters of trading strategies to maximize the trading profit on GPU from NVIDIA in the framework of the CUDA technology is discussed.
Keywords: trading strategies; parallel genetic algorithm; financial indicator; evolutionary computation.
Received: 15.10.2011
Document Type: Article
UDC: 681.324 + 519.17
Language: Russian
Citation: O. G. Monakhov, “Optimization of trading strategies by parallel evolutionary computation on graphics processing units”, Num. Meth. Prog., 13:1 (2012), 28–32
Citation in format AMSBIB
\Bibitem{Mon12}
\by O.~G.~Monakhov
\paper Optimization of trading strategies by parallel evolutionary computation on graphics processing units
\jour Num. Meth. Prog.
\yr 2012
\vol 13
\issue 1
\pages 28--32
\mathnet{http://mi.mathnet.ru/vmp4}
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