Distributionally robust mean-absolute deviation portfolio optimization using wasserstein metric

Data uncertainty has a great impact on portfolio selection. Based on the popular mean-absolute deviation (MAD) model, we investigate how to make robust portfolio decisions. In this paper, a novel Wasserstein metric-based data-driven distributionally robust mean-absolute deviation (DR-MAD) model is p...

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Detalles Bibliográficos
Autores principales: Chen, Dali, Wu, Yuwei, Li, Jingquan, Ding, Xiaohui, Chen, Caihua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9108021/
https://www.ncbi.nlm.nih.gov/pubmed/35601808
http://dx.doi.org/10.1007/s10898-022-01171-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9108021/
https://www.ncbi.nlm.nih.gov/pubmed/35601808
http://dx.doi.org/10.1007/s10898-022-01171-x

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