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undergraduate thesis
Predviđanje volatilnosti financijskih vremenskih nizova
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. urn:nbn:hr:168:576099
Milković, Jura
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Milković, J. (2022). Predviđanje volatilnosti financijskih vremenskih nizova (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:576099

Milković, Jura. "Predviđanje volatilnosti financijskih vremenskih nizova." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:576099

Milković, Jura. "Predviđanje volatilnosti financijskih vremenskih nizova." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:576099

Milković, J. (2022). 'Predviđanje volatilnosti financijskih vremenskih nizova', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 07 October 2024, https://urn.nsk.hr/urn:nbn:hr:168:576099

Milković J. Predviđanje volatilnosti financijskih vremenskih nizova [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 October 07] Available at: https://urn.nsk.hr/urn:nbn:hr:168:576099

J. Milković, "Predviđanje volatilnosti financijskih vremenskih nizova", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:576099

Metadata
TitlePredviđanje volatilnosti financijskih vremenskih nizova
Title (english)Financial Time Series Volatility Forecasting
AuthorJura Milković
MentorZvonko Kostanjčar (mentor)
Committee memberZvonko Kostanjčar (predsjednik povjerenstva)
Committee memberTomislav Kovačević (član povjerenstva)
Committee memberAndro Merćep (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-07-15, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Zbog uske povezanosti volatilnosti s rizikom ulaganja, javlja se potreba za njenim predviđanjem. Prethodno se pokazalo da su modeli strojnog učenja uspješniji od standardnih statističkih pristupa u brojnim znanstvenim disciplinama, što je motiviralo istraživanje modela strojno učenja za predviđanje volatilnosti. U ovom radu, isprobani su linearni modeli i modeli slučajnih šuma za predviđanje volatilnosti definirane na tri različita načina. Modeli su trenirani i testirani na povijesnim podatcima tri različite vrste financijske imovine: dionica, kriptovaluta i valutni par. Eksperimenti su pokazali da je najmanja srednja kvadratna pogreška postignuta za predviđanje varijance eksponencijalno otežanih povrata koristeći modele slučajnih šuma.
Abstract (english)
Since volatility is closely related to investment risk, there is a need for its prediction. Machine learning models have already proven to be more successful than standard statistical approaches in several scientific disciplines, which has motivated the exploration of machine learning models for volatility prediction. This paper tests linear models and random forest models for volatility prediction defined in three different ways. The models were trained and tested on historical data from three different types of financial assets: Stocks, cryptocurrencies, and currency pairs. The experiments showed that the smallest mean square error in predicting the variance of exponentially weighted returns is achieved with random forest models.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:576099
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 on2023-01-15 10:52:32