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undergraduate thesis
Predviđanje cijena dionica korištenjem LSTM mreže
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. urn:nbn:hr:168:725275
Radović, Filip
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Radović, F. (2019). Predviđanje cijena dionica korištenjem LSTM mreže (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:725275

Radović, Filip. "Predviđanje cijena dionica korištenjem LSTM mreže." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:725275

Radović, Filip. "Predviđanje cijena dionica korištenjem LSTM mreže." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:725275

Radović, F. (2019). 'Predviđanje cijena dionica korištenjem LSTM mreže', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 03 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:725275

Radović F. Predviđanje cijena dionica korištenjem LSTM mreže [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2019 [cited 2024 November 03] Available at: https://urn.nsk.hr/urn:nbn:hr:168:725275

F. Radović, "Predviđanje cijena dionica korištenjem LSTM mreže", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:168:725275

Metadata
TitlePredviđanje cijena dionica korištenjem LSTM mreže
Title (english)Predicting Stock Prices Using the LSTM Recurrent Neural Network
AuthorFilip Radović
MentorKlemo Vladimir (mentor)
Committee memberKlemo Vladimir (predsjednik povjerenstva)
Committee memberAdrian Satja Kurdija (član povjerenstva)
Committee memberDomagoj Alagić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2019-07-17, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Tema ovog rada je izrada LSTM modela za predviđanje cijena dionica. Na početku je dan kratki uvod u povijest ovog problema i u rješenja koja su do sada predložena. Opisani su klasični problemi s kojima se susrećemo pri izradi LSTM modela za predviđanje cijena dionica. Pokazan je način na koji se može izbjeći problem autokorelacije vremenskih serija koji uzrokuje netočne rezultate kod treniranja LSTM mreža. Opisana je tehnika kojom se mogu normalizirati podaci dionica. Prikazani su alternativni izvori podataka za predviđanje cijena dionica. Detaljno su opisane tehnike za uklanjanje šuma iz podataka poput wavelet transformacije i autoenkodera. Opisane su arhitekture korištenih mreža i algoritmi korišteni za njihovu optimizaciju. Testirane su različite kombinacije hiperparametara i objašnjeni rezultati koji su dobiveni pomoću njih.
Abstract (english)
The subject of this paper is the creation of an LSTM model for forecasting stock prices. The paper gives a brief introduction to the history of the problem and describes solutions that have been suggested so far. Classical problems that appear when forecasting stock prices with an LSTM model are described. A way to eliminate the problem arising from the auto-correlation of time series data is demonstrated. A successful normalization technique for stock data is described. Alternative data sources for forecasting stock prices are shown. Comprehensive descriptions of noise removal techniques from data such as wavelet transformation and autoencoders are given. The architecture of the networks and the algorithms used for their optimization are described. Various combinations of hyperparameters are explored, and the results obtained by using them are given.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:725275
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 on2020-01-07 21:44:22