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undergraduate thesis
Automatizirano trgovanje financijskom imovinom temeljem moving average convergence divergence (MACD) metode
Osijek: Josip Juraj Strossmayer University of Osijek, Department of Mathematics, 2021. urn:nbn:hr:126:792429
Žunić, Luka
Josip Juraj Strossmayer University of Osijek
Department of Mathematics

Institutional repository: Repository of School of Applied Mathematics and Informatics

Cite this document

Žunić, L. (2021). Automatizirano trgovanje financijskom imovinom temeljem moving average convergence divergence (MACD) metode (Undergraduate thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Department of Mathematics. Retrieved from https://urn.nsk.hr/urn:nbn:hr:126:792429

Žunić, Luka. "Automatizirano trgovanje financijskom imovinom temeljem moving average convergence divergence (MACD) metode." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Department of Mathematics, 2021. https://urn.nsk.hr/urn:nbn:hr:126:792429

Žunić, Luka. "Automatizirano trgovanje financijskom imovinom temeljem moving average convergence divergence (MACD) metode." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Department of Mathematics, 2021. https://urn.nsk.hr/urn:nbn:hr:126:792429

Žunić, L. (2021). 'Automatizirano trgovanje financijskom imovinom temeljem moving average convergence divergence (MACD) metode', Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Department of Mathematics, accessed 19 January 2025, https://urn.nsk.hr/urn:nbn:hr:126:792429

Žunić L. Automatizirano trgovanje financijskom imovinom temeljem moving average convergence divergence (MACD) metode [Undergraduate thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Department of Mathematics; 2021 [cited 2025 January 19] Available at: https://urn.nsk.hr/urn:nbn:hr:126:792429

L. Žunić, "Automatizirano trgovanje financijskom imovinom temeljem moving average convergence divergence (MACD) metode", Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Department of Mathematics, Osijek, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:126:792429

Metadata
TitleAutomatizirano trgovanje financijskom imovinom temeljem moving average convergence divergence (MACD) metode
Title (english)Algorithmic Trading Based on the Moving Average Convergence Divergence (MACD) Method
AuthorLuka Žunić
MentorNenad Šuvak (mentor)
GranterJosip Juraj Strossmayer University of Osijek
Department of Mathematics
Osijek
Defense date and country2021-09-28, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Mathematics
Mathematical Logic and Accounting
Abstract
Kada promatramo tržište kriptovaluta, ponuđeni su nam mnogi indikatori kojima se možemo služiti u kombinaciji s različitim strategijama da tako pokušamo poboljšati uspješnost trgovanja. U ovom radu će detaljnije biti opisan MACD indikator i načini na koje se može koristiti. Rad se sastoji od 6 poglavlja u kojima se govori o strukturi grafova koji prate vrijednosti kriptovaluta, izračunavanju jednostavnih i eksponencijalnih pomičnih prosjeka te samoj implementaciji i načinima na koje se može koristiti MACD.
Abstract (english)
When evaluating the cryptocurrency market, we have a lot of indicators which we can use in combination with different strategies as to improve the trading result. In this thesis the emphasis is on the MACD indicator and the ways it can be used. The thesis consists of 6 chapters in which we introduce the structure of candlestick graphs, the calculation of simple and exponential moving averages and the implementation of and the ways in which MACD can be used.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:126:792429
Study programmeTitle: Bachelor of Mathematics and Computer Science
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) matematike i računarstva (sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) matematike i računarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2021-10-11 07:30:30