Neural networks and their usage in stock market price prediction
Νευρωνικά δίκτυα και η χρήση τους στην πρόβλεψη τιμών χρηματιστηρίου
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Keywords
Neural networks ; Stock price prediction ; Time series forecasting ; Deep learning ; Tesla ; Machine learningAbstract
This postgraduate dissertation explores the use of artificial neural networks for predicting the stock price of Tesla. Deep learning models such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) networks are utilized, as they are well-suited for analyzing and forecasting time series data. The study includes the collection and preprocessing of historical stock data, the design and training of predictive models, and the evaluation of their performance using error metrics. The results indicate that LSTM models achieve improved accuracy compared to traditional forecasting methods, highlighting the potential of modern machine learning algorithms in financial time series prediction.
Postgraduate Studies Programme
Προηγμένα Συστήματα ΠληροφορικήςDepartment
Σχολή Τεχνολογιών Πληροφορικής και Επικοινωνιών. Τμήμα Ψηφιακών ΣυστημάτωνNumber of pages
67Language
EnglishCollections
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Αναφορά Δημιουργού-Όχι Παράγωγα Έργα 3.0 Ελλάδα
Αναφορά Δημιουργού-Όχι Παράγωγα Έργα 3.0 Ελλάδα