In this study we propose a stochastic mortality forecast model that may be viewed as a Levy process. First, age, period and cohort effects are objectively identified in a given matrix of historic mortality data. Next, these patterns are removed from the matrix of mortality improvement rates. We then forecast residual mortality development factors by applying a non-parametric block bootstrap simulation. Finally, future age, period and cohort effects are superimposed on a simulation basis. In a retrospective study we apply several backtests in order to evaluate ex-post predictive power of our model. Moreover, we evaluate plausibility of ex-ante forecasts. Notably, our stochastic mortality model is capable of generating specific stress scenarios such as mortality shocks. In this respect, our forecast model may be particularly useful for Solvency II purposes.