Lahiri, S.N. (1992) Edgeworth Correction by Moving Block Bootstrap for Stationary and Non Stationary Data. In: Lepage, R. and Billard, L., Eds., Exploring the Limits of Bootstrap, Wiley, New York, 225-248.

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.