prikaz prve stranice dokumenta Upotreba obrade prirodnog jezika za predviđanje tržišta dionica
No public access
master's thesis
Upotreba obrade prirodnog jezika za predviđanje tržišta dionica
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. urn:nbn:hr:168:714750
Puh, Karlo
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Puh, K. (2022). Upotreba obrade prirodnog jezika za predviđanje tržišta dionica (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:714750

Puh, Karlo. "Upotreba obrade prirodnog jezika za predviđanje tržišta dionica." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:714750

Puh, Karlo. "Upotreba obrade prirodnog jezika za predviđanje tržišta dionica." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:714750

Puh, K. (2022). 'Upotreba obrade prirodnog jezika za predviđanje tržišta dionica', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 26 June 2024, https://urn.nsk.hr/urn:nbn:hr:168:714750

Puh K. Upotreba obrade prirodnog jezika za predviđanje tržišta dionica [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 June 26] Available at: https://urn.nsk.hr/urn:nbn:hr:168:714750

K. Puh, "Upotreba obrade prirodnog jezika za predviđanje tržišta dionica", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:714750

Metadata
TitleUpotreba obrade prirodnog jezika za predviđanje tržišta dionica
Title (english)The Use of Natural Language Processing for Stock Market Prediction
AuthorKarlo Puh
MentorMarina Bagić Babac (mentor)
Committee memberMarina Bagić Babac (predsjednik povjerenstva)
Committee memberMirjana Domazet-Lošo (član povjerenstva)
Committee memberMarko Horvat (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-07-06, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Predviđanje cijena na burzi oduvijek je bila zanimljiva tema budući da je usko povezana sa zarađivanjem novca. Korištenje obrade prirodnog jezika otvorilo je nove perspektive za rješavanje ovog zadatka. U ovom su radu kao mjerilo implementirani konvencionalni statistički modeli za predviđanje vremenskih serija. Zatim, radi metodološke usporedbe, implementirani su i testirani različiti najsuvremeniji modeli obrade prirodnog jezika u rasponu od osnovnih CNN-a i RNN-a do najnaprednijih BERT modela. Eksperimentalni rezultati pokazuju da postoji korelacija između tekstualnih informacija u naslovima vijesti i predviđanja cijene dionica. Model temeljen na GRU ćeliji s jednim linearnim slojem koji uzima parove povijesnih cijena i ocjene sentimenta izračunate pomoću BERT-a postigao je najbolje rezultate.
Abstract (english)
Predicting the stock market’s prices has always been an interesting topic since its closely related to making money. The use of natural language processing has opened new perspectives for solving this task. In this paper, the conventional statistical models for time-series prediction are implemented as a benchmark. Then, for methodological comparison, various state-of-the-art natural language models ranging from the baseline CNN and RNN to the most advanced BERT models are implemented and tested. Experimental results show that there is a correlation between the textual information in the news headlines and stock price prediction. The model based on the GRU cell with one linear layer which takes pairs of the historical prices and the sentiment score calculated using BERT achieved the best results.
Keywords
Keywords (english)
Languageenglish
URN:NBNurn:nbn:hr:168:714750
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsClosed access
Terms of useLicence In copyright icon
Public note
Created on2023-01-13 15:57:53