Kernel Conditional Quantile Estimation for Stationary Processes with Application to Conditional Value-at-Risk

Posted: 10 Jul 2008

See all articles by Wei Biao Wu

Wei Biao Wu

University of Chicago

Keming Yu

Brunel University London - CARISMA: The Centre for the Analysis of Risk and Optimisation Modelling Applications

Gautam Mitra

Brunel University London - CARISMA: The Centre for the Analysis of Risk and Optimisation Modelling Applications

Date Written: Spring 2008

Abstract

The paper considers kernel estimation of conditional quantiles for both short-range and long-range-dependent processes. Under mild regularity conditions, we obtain Bahadur representations and central limit theorems for kernel quantile estimates of those processes. Our theory is applicable to many price processes of assets in finance. In particular, we present an asymptotic theory for kernel estimates of the value-at-risk (VaR) of the market value of an asset conditional on the historical information or a state process. The results are assessed based on a small simulation and are applied to AT&T monthly returns.

Keywords: asymptotic expansion, Bahadur representation, causal process, central limit theorem, kernel estimation, long-range dependence, quantile estimation, short-range dependence, value-at-risk

Suggested Citation

Wu, Wei Biao and Yu, Keming and Mitra, Gautam, Kernel Conditional Quantile Estimation for Stationary Processes with Application to Conditional Value-at-Risk (Spring 2008). Journal of Financial Econometrics, Vol. 6, Issue 2, pp. 253-270, 2008. Available at SSRN: https://ssrn.com/abstract=1157740 or http://dx.doi.org/nbm022

Wei Biao Wu (Contact Author)

University of Chicago ( email )

1101 East 58th Street
Chicago, IL 60637
United States

Keming Yu

Brunel University London - CARISMA: The Centre for the Analysis of Risk and Optimisation Modelling Applications

John Crank Building
Brunel University
Uxbridge, UB8 3PH
United Kingdom

Gautam Mitra

Brunel University London - CARISMA: The Centre for the Analysis of Risk and Optimisation Modelling Applications ( email )

John Crank Building
Brunel University
Uxbridge, UB8 3PH
United Kingdom

Register to save articles to
your library

Register

Paper statistics

Abstract Views
430
PlumX Metrics