Συγκριτική αξιολόγηση αλγορίθμων αποτίμησης των δικαιωμάτων προαίρεσης βασισμένων σε μεγάλα δεδομένα

Χάντζος, Ανδρέας; Chantzos, Andreas

dc.contributor.author	Χάντζος, Ανδρέας	el
dc.contributor.author	Chantzos, Andreas	en
dc.date.accessioned	2026-06-12T08:29:58Z
dc.date.available	2026-06-12T08:29:58Z
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/64927
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.32621
dc.rights	Default License
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/gr/	*
dc.subject	Δικαιώματα Προαίρεσης	el
dc.subject	Χρηματοικονομικά	el
dc.subject	Black–Scholes–Merton	en
dc.subject	Μεταβλητότητα	el
dc.subject	Αριθμητικές Μέθοδοι	el
dc.subject	Stohastic Calculus	en
dc.subject	Monte Carlo Simulation	en
dc.subject	Quantitative Finance	en
dc.subject	Option Greeks	en
dc.subject	Volatility Modeling	en
dc.title	Συγκριτική αξιολόγηση αλγορίθμων αποτίμησης των δικαιωμάτων προαίρεσης βασισμένων σε μεγάλα δεδομένα	el
heal.type	bachelorThesis
heal.classification	Computer Science	en
heal.language	el
heal.access	free
heal.recordProvider	ntua	el
heal.publicationDate	2025-09-01
heal.abstract	This thesis provides a comprehensive study of option pricing, combining theoretical foundations, numerical methods, and empirical data analysis. It begins with a structured introduction to financial derivatives, with particular emphasis on options, their economic role, and their payoff characteristics. Building on this basis, the work develops the mathematical framework of stochastic calculus, introduces the Black–Scholes–Merton model, and examines extensions such as binomial trees, finite differences, and Monte Carlo simulations, together with the role of option sensitivities (Greeks). Further emphasis is placed on volatility modeling, addressing the limitations of constant-volatility assumptions and analyzing alternative approaches such as local, stochastic, and hybrid volatility models. To support empirical evaluation, a custom data collection pipeline was implemented in Python, automating the retrieval and processing of equity and option market data. These datasets enable the benchmarking of pricing models and the construction of implied volatility surfaces. Finally, a practical application was developed in Python/Dash, providing an interac- tive environment for data exploration, volatility visualization, numerical convergence studies, and backtesting of option strategies. The results highlight both the theoretical coherence and the practical limitations of classical and modern pricing techniques, offering insights into their applicability across different market contexts.	en
heal.advisorName	Τσανάκας, Παναγιώτης	el
heal.committeeMemberName	Μαρινάκης, Γεώργιος	el
heal.committeeMemberName	Σταφυλοπάτης, Ανδρέας-Γεώργιος	el
heal.academicPublisher	Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών. Τομέας Τεχνολογίας Πληροφορικής και Υπολογιστών	el
heal.academicPublisherID	ntua
heal.numberOfPages	144 σ.	el
heal.fullTextAvailability	false
heal.fullTextAvailability	false