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This paper addresses a new uncertainty set - interval random uncertainty set for robust Value-at-Risk optimization. The form of interval random uncertainty set makes it suitable for capturing the downside and upside deviations of real-world data. These deviation measures capture distributional asymmetry and lead to better optimization results. We also apply our interval random chance-constrained programming...
This paper addresses the portfolio selection problem in a robust manner. In practice, it is difficult to collect all information to determine the precise bounds of the box uncertainty set used in robust portfolio optimization. To solve this problem, we introduce a novel uncertainty set: interval random uncertainty. We apply our interval random chance-constrained programming to robust semi-absolute...
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