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Advances in Mathematical Finance and Applications، جلد ۹، شماره ۱، صفحات ۲۶۱-۲۷۴
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عنوان انگلیسی Providing a hybrid strategy based on the theory of turbulence and price acceleration in the Iranian stock market
چکیده انگلیسی مقاله Stock prices are influenced by economic, technological, psychological and geopolitical factors. A review of the literature in this field shows that stochastic approaches, trend analysis and econometrics have been used to demonstrate stock market dynamics and price forecasting. However, these techniques cannot provide a comprehensive overview of market dynamics. Because they ignore the temporal relationship between these factors and are unable to understand their cumulative effects on prices. By integrating chaos theory and continuous data mining based on price acceleration, this study has eliminated these gaps by inventing a new price forecasting method called dynamic stock market recognition simulator and combining two methods: one is delay structures. Or gives time intervals to the data set, and the other is the method of selecting new variables for the market environment. The results showed that the method used can be used to predict the long-term stock price using a small data set with small dimensions.
کلیدواژه‌های انگلیسی مقاله stock price, Forecast, price acceleration, Chaos theory
نویسندگان مقاله Rohollah Hamidi |
Department of Financial Management, North Tehran Branch, Islamic Azad University, Tehran, Iran

Ali Saeedi |
Associate Professor, Department of Management, North Tehran Branch, Islamic Azad University, Tehran, Iran.

Mohammad Khodaei Valazaghard |
Department of Financial Management, Tehran North Branch, Islamic Azad University, Tehran, Iran

Mehdi Naghavi |
Department of Financial Management, North Tehran Branch, Islamic Azad University, Tehran, Iran

نشانی اینترنتی https://amfa.arak.iau.ir/article_708563_2644780b481cc323c5d41b8326ccb901.pdf
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