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This paper addresses the problem of utility maximization under uncertain parameters. In contrast with the classical approach, where the parameters of the model evolve freely within a given range, we constrain them via a penalty function. We show that this robust optimization process can be...
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framework is model-free and allows for stresses on the output such as (a) the mean and variance, (b) any distortion risk measure … including the Value-at-Risk and Expected-Shortfall, and (c) expected utility type constraints, thus making the reverse … sensitivity analysis framework suitable for risk models. …
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