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In this paper, we propose formulations and algorithms for robust portfolio optimization under both aleatory uncertainty (i.e., natural variability) and epistemic uncertainty (i.e., imprecise probabilistic information) arising from interval data. Epistemic uncertainty is represented using two...
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The objective of this paper is to extend the results on Pseudo Maximum Likelihood (PML) theory derived in Gourieroux …(1984) to PML4 and QGPML2 methods, respectively. An asymptotic theory is developed which shows, in particular, that the …
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Classical spatial autoregressive models share the same weakness as the classical linear regression models, namely it is not possible to estimate non-linear relationships between the dependent and independent variables. In the case of classical linear regression a semi-parametric approach can be...
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