FORECASTING FINANCIAL TIME SERIES USING A METHOD OF SELFORGANIZED CRITICALITY
There are four main methods of forecastingfinancial time series: technical analysis,mathematical analysis, fundamental analysis, the use of neural networks. Evolution of financial time series is accompanied by bifurcations, characterizing the internal propertiesof the system. Then there is the unstab...
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Plekhanov Russian University of Economics
2016-08-01
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doaj-390c6a8dc8e6437e96de73ab1839bdf52021-07-28T21:19:56ZrusPlekhanov Russian University of EconomicsStatistika i Èkonomika2500-39252016-08-010315315710.21686/2500-3925-2014-3-153-157444FORECASTING FINANCIAL TIME SERIES USING A METHOD OF SELFORGANIZED CRITICALITYMichail E. Mazurov0Moscow state University ofEconomics, statistics and Informatics (MESI)There are four main methods of forecastingfinancial time series: technical analysis,mathematical analysis, fundamental analysis, the use of neural networks. Evolution of financial time series is accompanied by bifurcations, characterizing the internal propertiesof the system. Then there is the unstable state and momentum, which is distributed in a distributed system stock exchanges. Giventhis mechanism to analyze the behaviorof financial time series, we use bifurcation theory and a system of nonlinear differential equations of parabolic type, which are thebasic equations in synergetics.https://statecon.rea.ru/jour/article/view/445прогнозирование фи нансовых временных рядовбифуркациисистемы нелинейных дифференциаль ных уравнений параболического типакомпьютерное моделированиеforecasting financial time seriesbifurcation of a system of nonlinear differential equations of parabolic typecomputersimulation |
collection |
DOAJ |
language |
Russian |
format |
Article |
sources |
DOAJ |
author |
Michail E. Mazurov |
spellingShingle |
Michail E. Mazurov FORECASTING FINANCIAL TIME SERIES USING A METHOD OF SELFORGANIZED CRITICALITY Statistika i Èkonomika прогнозирование фи нансовых временных рядов бифуркации системы нелинейных дифференциаль ных уравнений параболического типа компьютерное моделирование forecasting financial time series bifurcation of a system of nonlinear differential equations of parabolic type computersimulation |
author_facet |
Michail E. Mazurov |
author_sort |
Michail E. Mazurov |
title |
FORECASTING FINANCIAL TIME SERIES USING A METHOD OF SELFORGANIZED CRITICALITY |
title_short |
FORECASTING FINANCIAL TIME SERIES USING A METHOD OF SELFORGANIZED CRITICALITY |
title_full |
FORECASTING FINANCIAL TIME SERIES USING A METHOD OF SELFORGANIZED CRITICALITY |
title_fullStr |
FORECASTING FINANCIAL TIME SERIES USING A METHOD OF SELFORGANIZED CRITICALITY |
title_full_unstemmed |
FORECASTING FINANCIAL TIME SERIES USING A METHOD OF SELFORGANIZED CRITICALITY |
title_sort |
forecasting financial time series using a method of selforganized criticality |
publisher |
Plekhanov Russian University of Economics |
series |
Statistika i Èkonomika |
issn |
2500-3925 |
publishDate |
2016-08-01 |
description |
There are four main methods of forecastingfinancial time series: technical analysis,mathematical analysis, fundamental analysis, the use of neural networks. Evolution of financial time series is accompanied by bifurcations, characterizing the internal propertiesof the system. Then there is the unstable state and momentum, which is distributed in a distributed system stock exchanges. Giventhis mechanism to analyze the behaviorof financial time series, we use bifurcation theory and a system of nonlinear differential equations of parabolic type, which are thebasic equations in synergetics. |
topic |
прогнозирование фи нансовых временных рядов бифуркации системы нелинейных дифференциаль ных уравнений параболического типа компьютерное моделирование forecasting financial time series bifurcation of a system of nonlinear differential equations of parabolic type computersimulation |
url |
https://statecon.rea.ru/jour/article/view/445 |
work_keys_str_mv |
AT michailemazurov forecastingfinancialtimeseriesusingamethodofselforganizedcriticality |
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