Predviđanje cijena opcija pomoću modela binomnog stabla

undergraduate thesis

• Title (english): Option price prediction using a binomial tree model
• Author: Edi Prodan
• Mentor: Zvonko Kostanjčar (mentor)
• Committee member: Zvonko Kostanjčar (predsjednik povjerenstva)
• Committee member: Sven Goluža (član povjerenstva)
• Committee member: Tessa Bauman (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2023-07-06, 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: binomial options pricing model; CRR; option pricing; financial derivati- ves; Meta Platforms; American options; Python
• Keywords (english): binomial options pricing model; CRR; option pricing; financial derivatives; Meta Platforms; Python
• Language: croatian
• URN:NBN: urn:nbn:hr:168:914903
• Study programme: Title: 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 resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2023-10-11 10:14:20