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Problemy Upravleniya, 2016, Issue 5, Pages 41–46
(Mi pu991)
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This article is cited in 6 scientific papers (total in 6 papers)
Control in the socio-economic systems
Time series segmentation and hashing in the stock market prediction problems
A. G. Spiro, M. D. Goldovskaya, N. E. Kiseleva, I. V. Pokrovskaya V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, Moscow
Abstract:
It is suggested to associate each analyzed time series of exchange-traded asset price (TS-P) with time series of hash codes (TS-HK) that will show the price rising or falling for each element of TS-P. In this case the hash codes are integers, and their sequence allows similar (typical) groups of TS-P highlighting in exchange-traded asset price changing dynamics. Described are the procedures of the original time series conversion and of the corresponding hash codes determination. The basic properties of hash codes sequences are formulated. The methodology of trajectory analysis and the asset exchange rate forecasting is suggested, using segmentation and hashing data.
Keywords:
stock market, the procedure of a sliding window, the hash codes, time series segmentation, typical segments, the growth/falling forecasting of stock quotes.
Citation:
A. G. Spiro, M. D. Goldovskaya, N. E. Kiseleva, I. V. Pokrovskaya, “Time series segmentation and hashing in the stock market prediction problems”, Probl. Upr., 2016, no. 5, 41–46; Automation and Remote Control, 79:5 (2018), 911–918
Linking options:
https://www.mathnet.ru/eng/pu991 https://www.mathnet.ru/eng/pu/v5/p41
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Statistics & downloads: |
Abstract page: | 199 | Full-text PDF : | 114 | References: | 25 | First page: | 5 |
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