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<p>This article discusses nonparametric estimation of some conditional expectile-based risk measures using local polynomial fitting. The focus is on estimating conditional expectile-based Value-at-Risk and conditional expectile-based Expected Shortfall. Estimation of the latter is also discussed in a framework of heavy-tailed distributions, which involves a data-driven choice of the number of tail observations used in the estimation. The finite-sample performance of the proposed conditional risk measure estimators is investigated in a simulation study. The practical use of the developed methods is illustrated in three real data examples.</p>

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Nonparametric estimation of conditional expectile-based risk measures

  • 期刊论文

  • 发表日期：

    2025年9月11日

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  • C. Adam,
  • I. Gijbels

摘要

This article discusses nonparametric estimation of some conditional expectile-based risk measures using local polynomial fitting. The focus is on estimating conditional expectile-based Value-at-Risk and conditional expectile-based Expected Shortfall. Estimation of the latter is also discussed in a framework of heavy-tailed distributions, which involves a data-driven choice of the number of tail observations used in the estimation. The finite-sample performance of the proposed conditional risk measure estimators is investigated in a simulation study. The practical use of the developed methods is illustrated in three real data examples.