TY  - BOOK
AU  - Xu,Ke-li
TI  - Nonparametric inference for conditional quantiles of time series
SN  - 02664666
AV  - HB139.T52 ECO 
PY  - 2013///
CY  - Cambridge
PB  - Cambridge University Press
KW  - Time series analysis
KW  - Nonparametric statistics |
KW  - Theory
N2  - This paper considers model-free hypothesis testing and confidence interval construction for conditional quantiles of time series. A new method, which is based on inversion of the smoothed empirical likelihood of the conditional distribution function around the local polynomial estimator, is proposed. The associated inferential procedures do not require variance estimation, and the confidence intervals are automatically shaped by data. We also construct the bias-corrected empirical likelihood, which does not require undersmoothing. Limit theories are developed for mixing time series. Simulations show that the proposed methods work well in finite samples and outperform the normal confidence interval. An empirical application to inference of the conditional value-at-risk of stock returns is also provided
UR  - : https://doi.org/10.1017/S0266466612000667
ER  -