In this paper we study asymptotic consistency of law invariant convex risk measures and the corresponding risk averse stochastic programming problems for independent identically distributed data. Under mild regularity conditions we prove a Law of Large Numbers and epiconvergence of the corresponding statistical estimators. This can be applied in a straight forward way to establishing convergence w.p.1 of sample based estimators of risk averse stochastic programming problems.

## Citation

Preprint

## Article

View Consistency of sample estimates of risk averse stochastic programs