Dynamic Programming Principle for Stochastic Control Problems driven by General L\'evy Noise
Abstract
We extend the proof of the dynamic programming principle (DPP) for standard stochastic optimal control problems driven by general L\'evy noises. Under appropriate assumptions, it is shown that the DPP still holds when the state process fails to have any moments at all.
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