Department of Economics

We analyze a multistage stochastic asset allocation problem with decision rules. The uncertainty is modeled using economic scenarios with Gaussian and stable Paretian non-Gaussian innovations. The optimal allocations under these alternative hypothesis are compared. If the agent has very low or very high risk aversibility, then the Gaussian and stable non-Gaussian scenarios result in similar allocations. When the risk aversion of the agent is between these two extreme cases, then the two distributional assumptions result in very di�erent asset allocations. Our calculations suggest that the allocations may be up to 85% different depending on the level of risk aversion of the agent.