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Lahiri, S.N. (2003) Resampling Methods for Dependent Data. Springer-Verlag, New York.
https://doi.org/10.1007/978-1-4757-3803-2

has been cited by the following article:

• TITLE: Bootstrapping the Expected Shortfall

  AUTHORS: Shuxia Sun, Fuxia Cheng

  KEYWORDS: High Quantile, Risk Measure, Moving Block Bootstrap, Nonparametric Estimation, Strong Mixing Sample Quantile

  JOURNAL NAME: Theoretical Economics Letters, Vol.8 No.4, March 7, 2018

  ABSTRACT: The expected shortfall is a popular risk measure in financial risk management. It is defined as the conditional expected loss given that the loss is greater than a given high quantile. We derive the asymptotic properties of the blocking bootstrap estimators for the expected shortfall of a stationary process under strong mixing conditions.