High Quantile Estimation for some Stochastic Volatility Models
| dc.contributor.author | Luo, Ling | |
| dc.contributor.supervisor | Kulik, Rafal | |
| dc.contributor.supervisor | Zarepour, Mahmoud | |
| dc.date.accessioned | 2011-10-05T20:26:40Z | |
| dc.date.available | 2011-10-05T20:26:40Z | |
| dc.date.created | 2011 | |
| dc.date.issued | 2011 | |
| dc.degree.discipline | Sciences / Science | |
| dc.degree.level | masters | |
| dc.degree.name | MSc | |
| dc.description.abstract | In this thesis we consider estimation of the tail index for heavy tailed stochastic volatility models with long memory. We prove a central limit theorem for a Hill estimator. In particular, it is shown that neither the rate of convergence nor the asymptotic variance is affected by long memory. The theoretical findings are verified by simulation studies. | |
| dc.embargo.terms | immediate | |
| dc.faculty.department | Mathématiques et statistique / Mathematics and Statistics | |
| dc.identifier.uri | http://hdl.handle.net/10393/20295 | |
| dc.identifier.uri | http://dx.doi.org/10.20381/ruor-4885 | |
| dc.language.iso | en | |
| dc.publisher | Université d'Ottawa / University of Ottawa | |
| dc.subject | stochastic volatility | |
| dc.subject | long memory | |
| dc.title | High Quantile Estimation for some Stochastic Volatility Models | |
| dc.type | Thesis | |
| thesis.degree.discipline | Sciences / Science | |
| thesis.degree.level | Masters | |
| thesis.degree.name | MSc | |
| uottawa.department | Mathématiques et statistique / Mathematics and Statistics |
