Associative memory approach to modeling stock market trading patterns
The proposed research intends to use the ideas of stochastic Theory of Social Imitation (W. Weidlich, E. Calen and D. Shapiro, T. Vaga ), and of the associative memory approach to modeling the dynamical structure of polarization relationships (S. Levkov and A. Makarenko) for modeling the stock marke...
Збережено в:
| Дата: | 2007 |
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| Автори: | , , |
| Формат: | Стаття |
| Мова: | English |
| Опубліковано: |
Навчально-науковий комплекс "Інститут прикладного системного аналізу" НТУУ "КПІ" МОН та НАН України
2007
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| Теми: | |
| Онлайн доступ: | http://dspace.nbuv.gov.ua/handle/123456789/14081 |
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| Назва журналу: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Цитувати: | Associative memory approach to modeling stock market trading patterns / A. Makarenko, S. Levkov, V. Solia // Систем. дослідж. та інформ. технології. — 2007. — № 4. — С. 111-124. — Бібліогр.: 20 назв. — англ. |
Репозитарії
Digital Library of Periodicals of National Academy of Sciences of Ukraine| Резюме: | The proposed research intends to use the ideas of stochastic Theory of Social Imitation (W. Weidlich, E. Calen and D. Shapiro, T. Vaga ), and of the associative memory approach to modeling the dynamical structure of polarization relationships (S. Levkov and A. Makarenko) for modeling the stock market trading patterns. The method potentially will allow us to forecast the offer and demand dynamics of a particular security, and lead to modeling of the assets price behavior. Our approach is based on the attempt to utilize the principles of certain classes of neural networks to reveal and model the underlying structure of the real dynamical process. Also the models with internal structure of brokers are considered and results of computer experiments are discussed. |
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