Nonparametric expected shortfall forecasting incorporating weighted quantiles

@article{Storti2020NonparametricES,
  title={Nonparametric expected shortfall forecasting incorporating weighted quantiles},
  author={Giuseppe Storti and Chao Wang},
  journal={arXiv: Risk Management},
  year={2020}
}
A new semi-parametric Expected Shortfall (ES) estimation and forecasting framework is proposed. The proposed approach is based on a two step estimation procedure. The first step involves the estimation of Value-at-Risk (VaR) at different levels through a set of quantile time series regressions. Then, the ES is computed as a weighted average of the estimated quantiles. The quantiles weighting structure is parsimoniously parameterized by means of a Beta function whose coefficients are optimized… Expand

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