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Sibirskii Zhurnal Vychislitel'noi Matematiki, 2016, Volume 19, Number 2, Pages 195–205
DOI: https://doi.org/10.15372/SJNM20160206 (Mi sjvm612) 		 
This article is cited in 5 scientific papers (total in 5 papers)

Application of differential evolution algorithm for optimization of strategies based on financial time series

O. G. Monakhova, E. A. Monakhovaa, M. Pantb

a Institute of Computational Mathematics and Mathematical Geophysics SB RAS, 6 Lavrentiev pr., Novosibirsk, 630090, Russia
b Department of Applied Science and Engineering, New Technology Block, Saharanpur Campus of IIT, Roorkee, Saharanpur-247667, India
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DOI: https://doi.org/10.15372/SJNM20160206
Abstract: An approach to optimization of trading strategies (algorithms) based on indicators of financial markets and evolutionary computation is described. A new version of the differential evolution algorithm for the search for optimal parameters of trading strategies for the trading profit maximization is used. The experimental results show that this approach can considerably improve the profitability of the trading strategies.
Key words: trading strategy, parallel genetic algorithm, technical analysis, financial indicator, template, evolutionary computation.
Funding agency Grant number
Russian Foundation for Basic Research 14-01-92694 IND-a
Department of Science and Technology, India INT/RFBR/P-164
Received: 14.09.2015
English version:
Numerical Analysis and Applications, 2016, Volume 9, Issue 2, Pages 150–158
DOI: https://doi.org/10.1134/S1995423916020063
Bibliographic databases:
Document Type: Article
UDC: 519.85
Language: Russian
Citation: O. G. Monakhov, E. A. Monakhova, M. Pant, “Application of differential evolution algorithm for optimization of strategies based on financial time series”, Sib. Zh. Vychisl. Mat., 19:2 (2016), 195–205; Num. Anal. Appl., 9:2 (2016), 150–158
Citation in format AMSBIB
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    • This publication is cited in the following 5 articles:
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