Abstract
We study smoothed quantile estimator for a class of stationary processes. We obtain the convergency rates and the Bahadur representation, as well as the asymptotic normality for this estimator by the method of m-dependent approximation. Our results can be used in the study of the estimation of value-at-risk (VaR) and applied to many time series which have important applications in econometrics.
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Huang, C., Wang, H. & Lin, Z. Nonparametric estimation of quantiles for a class of stationary processes. Sci. China Math. 58, 2621–2632 (2015). https://doi.org/10.1007/s11425-015-5024-2
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DOI: https://doi.org/10.1007/s11425-015-5024-2