dc.contributor.author |
Соловйов, Володимир Миколайович |
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dc.contributor.author |
Saptsin, Vladimir |
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dc.contributor.author |
Chabanenko, Dmitry |
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dc.date.accessioned |
2017-07-26T14:39:36Z |
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dc.date.available |
2017-07-26T14:39:36Z |
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dc.date.issued |
2009-03 |
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dc.identifier.citation |
Soloviev V. N. Prediction of financial time series with the technology of high-order Markov chains [Electronic resources] / Vladimir Soloviev, Vladimir Saptsin, Dmitry Chabanenko // DPG Spring Meeting. Dresden, 22nd - 27th of March 2009. Working Group on Physics of Socio-economic Systems (AGSOE). – Drezden, 2009. – AGSOE 3.7. – Access mode : http://www.dpg-verhandlungen.de/year/2009/conference/dresden/static/agsoe.pdf |
uk |
dc.identifier.uri |
http://elibrary.kdpu.edu.ua/handle/0564/1131 |
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dc.identifier.uri |
https://doi.org/10.31812/0564/1131 |
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dc.description.abstract |
In this research the technology of complex Markov chains, i.e. Markov chains with a memory is applied to forecast the financial time-series. The high-order Markov chains can be simplified to first-order ones by
generalizing the states in Markov chains. Considering the *generalized state* as the sequence of states makes a possibility to model high-order Markov chains like first-order ones. The adaptive method of defining
the states is proposed, it is concerned with the statistic properties of price returns. The algorithm of prediction includes the next steps: (1) Generate the hierarchical set of time discretizations; (2) Reducing the discretiza-
tion of initial data and doing prediction at the every time-level (3) Recurrent conjunction of prediction series of different discretizations in a single time-series. The hierarchy of time discretizations gives a possibility to review long-memory properties of the series without increasing the order of the Markov chains, to make prediction on the different frequencies of the series. The technology is tested on several time-series, including: EUR/USD Forex course, the World’s indices, including Dow Jones, S&P 500, RTS, PFTS and other. |
uk |
dc.language.iso |
en |
uk |
dc.subject |
financial time series |
uk |
dc.subject |
high-order Markov chains |
uk |
dc.subject |
long-memory properties |
uk |
dc.title |
Prediction of financial time series with the technology of high-order Markov chains |
uk |
dc.type |
Article |
uk |