 Compound-Poisson annual loss quantile

Let annual losses be $L={\sum }_{i=1}^N{X}_i$ where $N\sim \mathrm{Poisson}(\lambda )$ is independent of an independent identically distributed sequence of nonnegative loss given default amounts of mean $\mu$ and variance ${\sigma }^2$. Conditional expectation and variance give $\mathbb{E}L=\lambda \mu$ and $\mathrm{Var}L=\lambda ({\sigma }^2+{\mu }^2)$. A many-event normal approximation yields the displayed quantile; the actual loss distribution has a zero atom and depends on the entire severity law. For rare events or extreme tails, the moment-based normal approximation need not be accurate.