The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Online Program Home
Abstract Details
|
Activity Number:
|
180
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Monday, July 30, 2012 : 10:30 AM to 12:20 PM
|
|
Sponsor:
|
IMS
|
| Abstract - #304404 |
|
Title:
|
On Tail Index Estimation Under Long Memory
|
|
Author(s):
|
Jan Beran*+ and Bikramjit Das and Dieter Schell
|
|
Companies:
|
University of Konstanz and ETH Zurich and University of Konstanz
|
|
Address:
|
Department of Mathematics and Statistics, University of Konstanz, Konstanz, , Germany
|
|
Keywords:
|
long memory ;
tail index ;
linear process ;
infinite variance ;
tail index estimation
|
|
Abstract:
|
In view of the practical importance of risk assessment, tail index estimation has been one of the most investigated topics in recent years. The situation where one observes time series with long memory and infinite variance is however less well explored. Here, we consider tail index estimation for linear processes with long memory and infinite variance. A simple robust procedure - originally designed for independent observations - is proposed. The asymptotic distribution of a left and right tail-index estimator respectively is derived under the assumption of symmetric stable innovations. An improved method combining the two estimators is also considered, together with tests for equality of tails.
|
The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
Back to the full JSM 2012 program
|
2012 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.