prikaz prve stranice dokumenta Analiza podataka o cijenama dionica
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undergraduate thesis
Analiza podataka o cijenama dionica
2020. urn:nbn:hr:168:433070
Novak, Helena
University of Zagreb
Faculty of Electrical Engineering and Computing

Cite this document

Novak, H. (2020). Analiza podataka o cijenama dionica (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:433070

Novak, Helena. "Analiza podataka o cijenama dionica." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:433070

Novak, Helena. "Analiza podataka o cijenama dionica." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:433070

Novak, H. (2020). 'Analiza podataka o cijenama dionica', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 29 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:433070

Novak H. Analiza podataka o cijenama dionica [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2020 [cited 2024 December 29] Available at: https://urn.nsk.hr/urn:nbn:hr:168:433070

H. Novak, "Analiza podataka o cijenama dionica", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:168:433070

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Metadata
TitleAnaliza podataka o cijenama dionica
Title (english)Analyzing Stock Prices Data
AuthorHelena Novak
MentorDamir Pintar (mentor)
Committee memberDamir Pintar (predsjednik povjerenstva)
Committee memberLuka Humski (član povjerenstva)
Committee memberLjiljana Brkić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2020-08-29, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U sklopu ovoga rada napravljena je analiza podataka o cijenama dionica te je objašnjen pojam vremenske serije. Zbog velike količine dostupnih podataka, podaci o cijenama dionica su zahvalno područje za analizu koja može biti ekonomski isplativa. U radu je detaljno objašnjena obrada podataka primjenom metoda statistike. Objašnjeni su modeli za predviđanje vremenskih serija i financijskih vremenskih nizova. Izgradnja modela je napravljena pomoću metoda strojnog učenja. Na slučaju predviđanja zaključnih cijena dionica s američkog tržišta prikazane su razlike između dva najčešća modela za prognoziranje vremenskih serija, a svi rezultati su prikazani grafički.
Abstract (english)
As part of this paper, an analysis of stock price data was made and the concept of time series was explained. Due to the large amount of data available, stock price data is a thankful area for analysis that can be economically viable. The paper explains in detail the data processing using statistical methods. Models for predicting time series and financial time series are explained. Building of models was done using machine learning methods. In the case of predicting closing stock prices from the US market, the differences between the two most common models for forecasting time series are shown, and all the results are shown graphically.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:433070
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 on2023-01-13 15:43:42