The value-at-risk (VaR) at a small level q, 0<q<1, is the size of the loss that occurs with a probability q. Semi-parametric partially reduced-bias (PRB) VaR-estimation procedures based on the mean-of-order-p of a set of k quotients of upper order statistics, with p any real number, are put forward. After the study of their asymptotic behavior, these PRB VaR-estimators are altogether compared with the classical ones for finite samples, through a large-scale Monte-Carlo simulation study. A brief application to financial log-returns is provided, as well as some final remarks.
|Journal||Communications in Statistics: Simulation and Computation|
|Publication status||Published - 2 Apr 2020|
- Heavy right tails
- Heuristic sample fraction selection; Monte-Carlo simulation; Semi-parametric estimation; Statistics of extremes; Value-at-risk estimation
- Primary 62G32; Secondary 65C05