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In this paper, we introduce a new approach for finding robust portfolios when there is model uncertainty. It differs from the usual worst‐case approach in that a (dynamic) portfolio is evaluated not only by its performance when there is an adversarial opponent (“nature”), but also by its performance relative to a stochastic benchmark. The benchmark corresponds to the wealth of a fictitious benchmark investor...
In this paper, we consider robust intensity control of a stochastic discrete event system. We introduce the notion of generalized relative entropy and extend the classical “entropy-based” approached to stochastic robust control by allowing for different levels of model uncertainty for different parts of the model. We also introduce a new class of risk-sensitive control problems which are characterized...
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