| dc.contributor.author |
Luo, Ling |
|
| dc.date.accessioned |
2011-10-05T20:26:40Z |
|
| dc.date.available |
2011-10-05T20:26:40Z |
|
| dc.date.created |
2011 |
en_US |
| dc.date.issued |
2011-10-05 |
|
| dc.identifier.uri |
http://hdl.handle.net/10393/20295 |
|
| 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. |
en_US |
| dc.language.iso |
en |
en_US |
| dc.subject |
stochastic volatility |
en_US |
| dc.subject |
long memory |
en_US |
| dc.title |
High Quantile Estimation for some Stochastic Volatility Models |
en_US |
| dc.type |
Thèse / Thesis |
en_US |
| dc.faculty.department |
Mathématiques et statistique / Mathematics and Statistics |
en_US |
| dc.contributor.supervisor |
Kulik, Rafal |
|
| dc.contributor.supervisor |
Zarepour, Mahmoud |
|
| dc.embargo.terms |
immediate |
en_US |
| dc.degree.name |
MSc |
en_US |
| dc.degree.level |
masters |
en_US |
| dc.degree.discipline |
Sciences / Science |
en_US |
