An important tool in risk management is the implementation of risk measures. We study dynamic models where risk measures and dynamic risk measures can be applied. In particular, we solve various portfolio optimization problems and introduce a class of dynamic risk measures via the notion of Markov decision processes. Using Bayesian control theory we furthermore derive an extension of the latter setting when we face model uncertainty.

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