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undergraduate thesis
Model optimizacije portfelja zasnovan na predviđanju trendova
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. urn:nbn:hr:168:368838
Šimek, Filip
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Šimek, F. (2020). Model optimizacije portfelja zasnovan na predviđanju trendova (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:368838

Šimek, Filip. "Model optimizacije portfelja zasnovan na predviđanju trendova." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:368838

Šimek, Filip. "Model optimizacije portfelja zasnovan na predviđanju trendova." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:368838

Šimek, F. (2020). 'Model optimizacije portfelja zasnovan na predviđanju trendova', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 11 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:368838

Šimek F. Model optimizacije portfelja zasnovan na predviđanju trendova [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2020 [cited 2024 July 11] Available at: https://urn.nsk.hr/urn:nbn:hr:168:368838

F. Šimek, "Model optimizacije portfelja zasnovan na predviđanju trendova", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:168:368838

Metadata
TitleModel optimizacije portfelja zasnovan na predviđanju trendova
Title (english)Portfolio Optimization Model Based on Trend Prediction
AuthorFilip Šimek
MentorZvonko Kostanjčar (mentor)
Committee memberZvonko Kostanjčar (predsjednik povjerenstva)
Committee memberTomislav Kovačević (član povjerenstva)
Committee memberStjepan Begušić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2020-07-09, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U ovome radu naslova Model optimizacije portfelja zasnovan na predviđanju trendova razvili smo dvije metode procjenjivanja budućih očekivanih povrata i implementirali ih u Markowitzev (Mean-Variance) model optimizacije portfelja. Napravili smo usporednu analizu performansi dobivenih efikasnih portfelja pomoću okvira za algoritamsko trgovanje mercury, a korištenjem dvije razvijene metode i treće, široko poznate, metode procjenjivanja povrata preko njihovog prosjeka u prošlosti koja se koristi u Mean Reversion strategiji trgovanja. Naše razvijene metode spadaju pod strategiju trgovanja praćenjem trendova (eng. trend-trading), a indikatori koje koristimo za otkrivanje trendova su l1 i Hodrick-Prescott filtri. Dobiveni rezultati testiranja nam pokazuju kako obje razvijene metode ostvaruju bolje performanse od trećeg korištenog modela (tzv. Mean portfelja) te S&P500 indeksa na promatranom razdoblju od 1990. do 2018. godine
Abstract (english)
In this paper entitled Portfolio Optimization Model Based on Trend Prediction, we have developed two methods for estimating future expected returns and implemented them in Markowitz (Mean-Variance) portfolio optimization model. We made a comparative analysis of the generated efficient portfolios performances using the mercury algorithmic trading framework, using two developed methods and a third, widely known, method of estimating returns over their average in the past used in the Mean Reversion trading strategy. Our developed methods fall under the trend-trading strategy, and the indicators we use to detect trends are l1 and Hodrick-Prescott filters. The obtained test results show us that both developed methods achieve better performances than the third used model (our so-called Mean portfolio) and the S&P500 index in the observed period from 1990. to 2018.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:368838
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 16:16:02