Bias correction for estimated distortion risk measure using the bootstrap

  title={Bias correction for estimated distortion risk measure using the bootstrap},
  author={J. Kim},
  journal={Insurance Mathematics & Economics},
  • J. Kim
  • Published 2010
  • Mathematics
  • Insurance Mathematics & Economics
  • The bias of the empirical estimate of a given risk measure has recently been of interest in the risk management literature. In particular, Kim and Hardy (2007) showed that the bias can be corrected for the Conditional Tail Expectation (CTE, a.k.a. Tail-VaR or Expected Shortfall) using the bootstrap. This article extends their result to the distortion risk measure (DRM) class where the CTE is a special case. In particular, through the exact bootstrap, it is analytically proved that the bias of… CONTINUE READING
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