Conference proceedings

Stock Price Forecasting Using Artificial Neural Networks

Year:

2025

Published in:

Taras Shevchenko National University of Kyiv
Forecasting Model
Data pPreparation
Stock Price Forecasting

This 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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19 publications found

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Publisher: Taras Shevchenko National University of Kyiv

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Development Of Models And Information Technology For Predicting Tv Viewing Metrics Using Data Science Methods

Publisher: Slovak University of Technology in Bratislava

Authors: Oleksandr Ilchuk, Ihor Miroshnychenko

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Forecasting Electricity Generation From Renewable Sources In Developing Countries (On The Example Of Ukraine)

Publisher: Neuro-Fuzzy Modeling Techniques in Economics

Authors: Ihor Miroshnychenko, Тetiana Kravchenko, Yuliia Drobyna

2025
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Comparison Of Machine Learning Methods For Emotional Analysis

Publisher: Taras Shevchenko National University of Kyiv

Authors: Ihor Miroshnychenko, Vladyslav Pelishenko

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Комплекс Моделей Оцінювання Інвестиційного Потенціалу Країни

Publisher: МОН

Authors: Ihor Miroshnychenko

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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