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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| Main Author: | |
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| Format: | Article |
| Language: | Russian |
| Published: |
Plekhanov Russian University of Economics
2016-08-01
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| Series: | Статистика и экономика |
| Subjects: | |
| Online Access: | https://statecon.rea.ru/jour/article/view/445 |
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| Summary: | 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. |
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| ISSN: | 2500-3925 |