Abstract:By considering the effect of long‐ and short‐run correlation (LS) networks, we propose an LS network‐augmented parametric portfolio selection model (LSNA‐PP). First, we combine the dynamic conditional correlation‐mixed data sampling (DCC‐MIDAS) model with the planar maximally filtered graph (PMFG) method to construct LS networks and extract network topological characteristics. Second, we design portfolio weights as a function of these topological characteristics to construct the LSNA‐PP model. Third, we apply … Show more
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