Segmentation and Hashing of Time Series in Stock Market Prediction
- Autores: Spiro A.G.1, Gol’dovskaya M.D.1, Kiseleva N.E.1, Pokrovskaya I.V.1
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Afiliações:
- Trapeznikov Institute of Control Sciences
- Edição: Volume 79, Nº 5 (2018)
- Páginas: 911-918
- Seção: Control Sciences
- URL: https://journals.rcsi.science/0005-1179/article/view/150904
- DOI: https://doi.org/10.1134/S0005117918050119
- ID: 150904
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Resumo
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.
Sobre autores
A. Spiro
Trapeznikov Institute of Control Sciences
Autor responsável pela correspondência
Email: arn.spi@mail.ru
Rússia, Moscow
M. Gol’dovskaya
Trapeznikov Institute of Control Sciences
Email: arn.spi@mail.ru
Rússia, Moscow
N. Kiseleva
Trapeznikov Institute of Control Sciences
Email: arn.spi@mail.ru
Rússia, Moscow
I. Pokrovskaya
Trapeznikov Institute of Control Sciences
Email: arn.spi@mail.ru
Rússia, Moscow
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