Central limit theorem and almost sure results for the empirical estimator of superquantiles/CVaR in the stationary case
نویسندگان
چکیده
In this paper, we show that the difference between empirical estimator and Conditional value-at-risk can be written as a simple partial sum + residual term. Starting from decomposition, prove central limit theorem some almost sure results for estimator, large class of stationary sequences. We also construct confidence interval with asymptotic level 1−α, study its coverage through two different sets simulation.
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Let {Xn; n ≥ 1} be a standardized non-stationary Gaussian sequence, and let denote Sn ∑n k 1 Xk , σn √ Var Sn . Under some additional condition, let the constants {uni; 1 ≤ i ≤ n, n ≥ 1} satisfy ∑n i 1 1−Φ uni → τ as n → ∞ for some τ ≥ 0 and min1≤i≤n uni ≥ c logn , for some c > 0, then, we have limn→∞ 1/ logn ∑n k 1 1/k I{∩i 1 Xi ≤ uki , Sk/σk ≤ x} e−τΦ x almost surely for any x ∈ R, where I A ...
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ژورنال
عنوان ژورنال: Statistics
سال: 2022
ISSN: ['1029-4910', '0233-1888', '1026-7786']
DOI: https://doi.org/10.1080/02331888.2022.2043325