JSM 2005 - Toronto

Abstract #303138

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 68
Type: Contributed
Date/Time: Sunday, August 7, 2005 : 4:00 PM to 5:50 PM
Sponsor: Section on Risk Analysis
Abstract - #303138
Title: Nonparametric Inference of Value at Risk for Dependent Financial Returns
Author(s): Song Xi Chen+ and Chengyong Tang*+
Companies: Iowa State University and Iowa State University
Address: , , , 3010 Regencey Ct Apt 30, Ames, IA, 50010, United States
Keywords: mixing ; kernel estimation ; standard error estimation
Abstract:

Theoretical properties of the kernel Value at Risk (VaR) estimator are investigated in the context of dependence. The presence of dependence affects the variance of the VaR estimates and has to be taken into consideration in order to obtain adequate assessment of their variation. An estimation procedure of the standard errors is proposed based on kernel estimation of the spectral density of a derived series. The performance of the VaR estimators and the proposed standard error estimation procedure are evaluated by theoretical investigation, simulation of commonly used models for financial returns, and empirical studies on real financial return series.

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Revised March 2005