Di Somma, Vittorio (2019) Monte Carlo methods for barrier options. [Tesi di dottorato]


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Item Type: Tesi di dottorato
Lingua: English
Title: Monte Carlo methods for barrier options.
Di Somma, Vittoriovittorio.disomma@unina.it
Date: 11 December 2019
Number of Pages: 72
Institution: Università degli Studi di Napoli Federico II
Department: Scienze Economiche e Statistiche
Dottorato: Economia
Ciclo di dottorato: 32
Coordinatore del Corso di dottorato:
Pagano, Marcomarco.pagano@unina.it
Di Lorenzo, EmiliaUNSPECIFIED
Toraldo, GerardoUNSPECIFIED
Cuomo, SalvatoreUNSPECIFIED
Date: 11 December 2019
Number of Pages: 72
Uncontrolled Keywords: Barrier options; Monte Carlo methods; Bayesian statistics
Settori scientifico-disciplinari del MIUR: Area 13 - Scienze economiche e statistiche > SECS-S/01 - Statistica
Area 13 - Scienze economiche e statistiche > SECS-S/06 - Metodi matematici dell'economia e delle scienze attuariali e finanziarie
Date Deposited: 14 Jan 2020 16:40
Last Modified: 17 Nov 2021 12:04
URI: http://www.fedoa.unina.it/id/eprint/12982


This thesis focuses the attention on a very common class of Monte Carlo methods to price a barrier option, named standard Monte Carlo methods, and on their issues: the bias and the high variance. In order to overcome these issues, in this thesis we describe a particular class of statistical procedures, named Bayesian Monte Carlo methods. The thesis is divided into two parts: in the first part we present the main Bayesian Monte Carlo methods under the Black-Scholes model, in the second part we generalize these schemes under the assumption of stochastic volatility. As supported by numerical experiments, a Bayesian Sequential Monte Carlo estimator is unbiased and has a lower variance than a standard Monte Carlo one.


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