In this paper, we prove a result for the asymptotic distribution of the sample average value-at-risk (AVaR) under certain regularity assumptions. The asymptotic distribution can be used to derive asymptotic confidence intervals when AV aR∈(X) is calculated by the Monte Carlo method which is adopted in many risk management systems. We study the effect of the tail behavior of the random variable X on the convergence rate and the improvement of a tail truncation method.
|Number of pages||18|
|Journal||Journal of Computational Analysis and Applications|
|State||Published - Oct 1 2008|
- Asymptotic distribution
- Average value-at-risk
- Monte Carlo
- Risk measures