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Wilks confidence regions for empirical weighted quantiles

  • Kaiko – Quantitative Data

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Abstract

Quantiles are fundamental tools in statistics and risk analysis. While asymptotic and finite-sample results for standard empirical quantiles are well established, analogous results for weighted quantiles remain scarce. In this paper, we establish a comprehensive asymptotic theory for weighted quantiles. We derive a multivariate central limit theorem for multiple perturbed weighted quantiles. This result yields, as corollaries, (i) a multivariate CLT for weighted empirical quantiles, (ii) an asymptotically distribution-free confidence interval for weighted quantiles in the spirit of Wilks’ method, and (iii) Wilks confidence bounds for the weighted expected shortfall. Our theoretical contributions are also supported by numerical experiments, which code is publicly available at https://github.com/michael-allouche/confidence-region-weighted-quantile .

Original languageEnglish
Article number110795
JournalStatistics and Probability Letters
Volume236
DOIs
Publication statusPublished - 1 Sept 2026

Keywords

  • Central limit theorem
  • Confidence intervals
  • Weighted quantiles
  • Wilks’ method

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