Algorithm of Trading on the Stock Market, Providing Satisfactory Results

Alexander Rubchinsky and Kristina Baikova
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Alexander Rubchinsky: National Research University (HSE)
Kristina Baikova: National University of Science and Technology (MISIS)

A chapter in Data Analysis and Optimization, 2023, pp 331-347 from Springer

Abstract: Abstract The paper proposes a new trading algorithm for S&P − 500 stock market, which provides positive results over a sufficiently long period of time. No assumptions are made about the behave-or of this market (including probabilistic ones) and no predictions are made and used. The daily real stock price data are considered and the gain (or loss) that would be obtained if the proposed stock choice algorithm for the next day was applied, is calculated. The algorithm uses only the closing price data for the preceding days and includes a special stopping rule based on the income, accumulated since an initial day of a considered period till a current day. The suggested algorithm substantially uses the previously developed approach to construction a family of graph decompositions (see publications Rubchinsky A, Family of graph decompositions and its applications to data analysis: working paper WP7/2016/09 – Moscow: Higher School of Economics Publ. House, 2016. – (Series WP7 “Mathematical methods for decision making in economics, business and politics”). p 60, 2016; Rubchinsky A, A new approach to network decomposition problems. In: Kalyagin V., Nikolaev A., Pardalos P., Prokopyev O. (eds) Models, algorithms, and technologies for network analysis. NET 2016. Springer Proceedings in Mathematics & Statistics, vol 197. Springer, Cham, 2017; Rubchinsky A, Graph dichotomy algorithm and its applications to analysis of stocks market. In: Kalyagin V., Pardalos P., Prokopyev O., Utkina I. (eds) Computational aspects and applications in large-scale networks. NET 2017. Springer Proceedings in Mathematics & Statistics, vol 247. Springer, Cham, 2018).

Keywords: Stock market; Graph decomposition; Trading algorithm; Cluster; Stopping rule; Secretary problem; Fractal (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-031-31654-8_20

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DOI: 10.1007/978-3-031-31654-8_20

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