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undergraduate thesis
Predviđanje cijena opcija pomoću modela binomnog stabla
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. urn:nbn:hr:168:914903
Prodan, Edi
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Prodan, E. (2023). Predviđanje cijena opcija pomoću modela binomnog stabla (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:914903

Prodan, Edi. "Predviđanje cijena opcija pomoću modela binomnog stabla." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:914903

Prodan, Edi. "Predviđanje cijena opcija pomoću modela binomnog stabla." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:914903

Prodan, E. (2023). 'Predviđanje cijena opcija pomoću modela binomnog stabla', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 17 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:914903

Prodan E. Predviđanje cijena opcija pomoću modela binomnog stabla [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2024 July 17] Available at: https://urn.nsk.hr/urn:nbn:hr:168:914903

E. Prodan, "Predviđanje cijena opcija pomoću modela binomnog stabla", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:914903

Metadata
TitlePredviđanje cijena opcija pomoću modela binomnog stabla
Title (english)Option price prediction using a binomial tree model
AuthorEdi Prodan
MentorZvonko Kostanjčar (mentor)
Committee memberZvonko Kostanjčar (predsjednik povjerenstva)
Committee memberSven Goluža (član povjerenstva)
Committee memberTessa Bauman (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2023-07-06, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Ovaj rad istražuje model binomnog stabla za predviđanje cijene opcija koristeći povijesne podatke sastavnica indeksa S&P 500. Opcije su važni financijski derivati koji se koriste za smanjenje rizika. Jedan od načina računanja poštene cijene opcije je diskretni model binomnog stabla. Cilj ovog istraživanja je precizno odrediti poštene cijene opcija te usporediti ih sa stvarnim tržišnim cijenama. Istraživanje je provedeno na američkim opcijama za dionice „Meta Platforms", a implementacija modela ostvarena je upotrebom programskog jezika Python. Analiziraju se različiti aspekti modela, uključujući točnost za „call" i „put" opcije te „in the money" i „out of the money" opcije. Također se istražuje utjecaj datuma dospijeća i cijene izvršavanja na točnost modela. Nadalje, analizira se isplativost opcija u različitim periodima. Unatoč inherentnim ograničenjima modela binomnog stabla, rezultati istraživanja ukazuju na njegovu učinkovitost, otvarajući prostor za daljnji napredak.
Abstract (english)
This paper explores the binomial options pricing model for predicting option prices using historical data of S&P 500 index components. Options are important financial derivatives used for risk reduction. One of the methods for calculating the fair value of an option is the discrete-time binomial options pricing model. The objective of this research is to accurately determine the fair prices of options and compare them with actual market prices. The study focuses on American options on Meta Platforms stock, and the model implementation is done using the Python programming language. Various aspects of the model are analyzed, including the accuracy for call and put options, as well as "in the money" and "out of the money" options. The influence of expiration dates and exercise prices on the model’s accuracy is also investigated. Furthermore, the profitability of options is examined over different time periods. Despite the inherent limitations of the binomial tree model, the research results indicate its effectiveness, leaving room for further advancements.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:914903
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)
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Created on2023-10-11 10:14:20