Automation and Remote Control

, Volume 79, Issue 5, pp 911–918 | Cite as

Segmentation and Hashing of Time Series in Stock Market Prediction

  • A. G. SpiroEmail author
  • M. D. Gol’dovskaya
  • N. E. Kiseleva
  • I. V. Pokrovskaya
Control Sciences


In this paper, we associate each time series of a stock price (TS-P) in a stock market with a time series of hash codes (TS-HC) that indicate price increase or decrease for each element of the TS-P. As noted, in this case hash codes represent integer numbers and their sequence allows to identify the same (typical) groups of TS-P elements in the stock price dynamics. We describe the procedures for transforming an initial time series and calculating the hash codes. The main properties of a sequence of hash codes are established. Finally, we suggest an analysis and prediction method for a stock price trajectory using segmentation and hashing data.


stock market sliding window hash codes segmentation of time series typical segment rise or decline prediction for market quotations 


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Copyright information

© Pleiades Publishing, Ltd. 2018

Authors and Affiliations

  • A. G. Spiro
    • 1
    Email author
  • M. D. Gol’dovskaya
    • 1
  • N. E. Kiseleva
    • 1
  • I. V. Pokrovskaya
    • 1
  1. 1.Trapeznikov Institute of Control SciencesRussian Academy of SciencesMoscowRussia

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