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undergraduate thesis
Procjena kretanja cijena dionica neuronskim mrežama
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. urn:nbn:hr:168:189510
Kožul, Tomislav
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Kožul, T. (2023). Procjena kretanja cijena dionica neuronskim mrežama (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:189510

Kožul, Tomislav. "Procjena kretanja cijena dionica neuronskim mrežama." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:189510

Kožul, Tomislav. "Procjena kretanja cijena dionica neuronskim mrežama." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:189510

Kožul, T. (2023). 'Procjena kretanja cijena dionica neuronskim mrežama', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 15 August 2024, https://urn.nsk.hr/urn:nbn:hr:168:189510

Kožul T. Procjena kretanja cijena dionica neuronskim mrežama [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2024 August 15] Available at: https://urn.nsk.hr/urn:nbn:hr:168:189510

T. Kožul, "Procjena kretanja cijena dionica neuronskim mrežama", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:189510

Metadata
TitleProcjena kretanja cijena dionica neuronskim mrežama
Title (english)Estimating the share price movement with neural networks
AuthorTomislav Kožul
MentorMarko Đurasević (mentor)
Committee memberMarko Đurasević (predsjednik povjerenstva)
Committee memberNikolina Frid (član povjerenstva)
Committee memberJosip Šarić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2023-07-06, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Rad obuhvaća izradu modela neuronske mreže koja koristi ćelije s dugoročnom memorijom (LSTM ćelije) za pronalaženje pravilnosti i uzoraka u kretanju cijena dionica. Dobiveni model implementiran je u skriptu koja, nakon što korisnik unese simbol dionice ili fonda čiju cijenu želi predvidjeti, preuzima podatke o aktualnim cijenama, obrađuje ih te predikcije prikazuje u numeričkom i grafičkom obliku. S ciljem pronalaska modela čije predikcije imaju najmanja odstupanja od stvarnih cijena, ispitane su različite arhitekture neuronskih mreža, kao i različite duljine ulaznih podataka. Dok je model učen i ispitan isključivo na povijesnim podacima, skripta model koristi za rad s tekućim vrijednostima.
Abstract (english)
The paper includes the construction of a neural network model that uses cells with long short-term memory (LSTM cells) to find regularities and patterns in stock price movements. The obtained model is implemented into a script that, after the user enters the symbol of the stock or fund whose price he wants to predict, downloads data on current prices, processes it, and displays the predictions in numerical and graphical format. To find a model whose predictions have the smallest deviations from the actual values, different architectures of neural networks were tested, as well as different lengths of input data. While the model was trained and tested exclusively on historical data, the script uses the model to work with current values.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:189510
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2023-10-11 09:23:27