Asymptotic properties of conditional value-at-risk estimate for asymptotic negatively associated samples.

This article examines the strong consistency of the conditional value-at-risk (CVaR) estimate for asymptotic negatively associated (ANA or ρ − , for short) random samples under mild conditions. It is demonstrated that the optimal rate can achieve nearly O (n − 1 / 2) under certain appropriate conditions. Furthermore, we present numerical simulations and a real data example to corroborate our theoretical results based on finite samples. [ABSTRACT FROM AUTHOR]