Stock Price Forecasting Using Artificial Neural Networks
Year:
2025Published in:
Taras Shevchenko National University of KyivThis study aims to develop a methodology for forecasting stock prices using machine learning methods, specifically Artificial Neural Networks (ANN), to improve prediction accuracy and support investment decision-making. The model implementation allows for short- and long-term forecasts over 1 month, 6 months, 1 year, and 5 years, enabling a range of forecasting horizons.
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Publisher: Taras Shevchenko National University of Kyiv
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Publisher: IT&I
Authors: Ihor Miroshnychenko, Vadym Ziuziun, Tetiana Kmytiuk, Nataliia Datsenko, Anna Kolomiiets
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Publisher: Scientific Perspectives
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Development Of Data Science Technologies In The Field Of Climate Change Research
Publisher: Taras Shevchenko National University of Kyiv
Authors: Ihor Miroshnychenko, Andrii Ukrainets
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Publisher: Інвестиції: практика та досвід
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Publisher: Slovak University of Technology in Bratislava
Authors: Oleksandr Ilchuk, Ihor Miroshnychenko
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Publisher: Neuro-Fuzzy Modeling Techniques in Economics
Authors: Ihor Miroshnychenko, Тetiana Kravchenko, Yuliia Drobyna
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Publisher: Taras Shevchenko National University of Kyiv
Authors: Ihor Miroshnychenko, Vladyslav Pelishenko
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Publisher: МОН
Authors: Ihor Miroshnychenko
Risk And Return For Cryptocurrencies As Alternative Investment: Kohonen Maps Clustering
Publisher: Neuro-Fuzzy Modeling Techniques in Economics
Authors: Ihor Miroshnychenko, Andrii Kaminskyi, Kostiantyn Pysanets