Di Somma, Vittorio (2019) Monte Carlo methods for barrier options. [Tesi di dottorato]
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| Item Type: | Tesi di dottorato |
|---|---|
| Resource language: | English |
| Title: | Monte Carlo methods for barrier options. |
| Creators: | Creators Email Di Somma, Vittorio vittorio.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: | nome email Pagano, Marco marco.pagano@unina.it |
| Tutor: | nome email Di Lorenzo, Emilia UNSPECIFIED Toraldo, Gerardo UNSPECIFIED Cuomo, Salvatore UNSPECIFIED |
| Date: | 11 December 2019 |
| Number of Pages: | 72 |
| 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 |
Collection description
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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