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- W2214593275 abstract "This paper provides a method to assess the model risk that is inherent in factor models. Specifically, we derive sharp and approximate bounds for tail risk measures of portfolio sums when besides knowledge of the marginal distributions of the components Xi we also have information on the influence of a risk factor Z on the individual risks Xi. The availability of this additional information makes it possible to improve considerably the standard bounds that are solely based on information on the marginal distributions. We develop the necessary tools to calculate sharp and approximate bounds for VaR and TVaR. As a general result, we obtain that a common risk factor reduces the dependence uncertainty. In particular, when Z induces positive dependence among (Xi)i, we get a significant improvement of the lower risk bounds. When Z induces negative dependence then we obtain a reduction of the upper risk bounds." @default.
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- W2214593275 date "2015-01-01" @default.
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- W2214593275 title "Risk Bounds for Factor Models" @default.
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- W2214593275 doi "https://doi.org/10.2139/ssrn.2572508" @default.
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