Search
Login

Modeling portfolio efficiency using stochastic optimization with incomplete information and partial uncertainty

Abstract
Abstract Efficiency plays a crucial role in portfolio optimization. This notion is formulated by means of stochastic optimization techniques. Very often this problem is subject to partial uncertainty or incomplete information on the probability distribution and on the preferences expressed by means of the utility function. In this case both the objective function and the underlying probability measure are not known with precision. To address this kind of issues we propose to model the notion of incomplete information by means of set-valued analysis and therefore we propose two different extensions of the classical model. In the first one we rely on the notion of set-valued function while the second one utilizes the notion of set-valued probability. For both of them we investigate stability properties. These results are also linked to the notion of robustness of the aforementioned problem. Finally we apply the obtained results to portfolio theory and stochastic dominance.
Authors
D. Torre F. Mendivil and M. Rocca D. Torre: Université Côte d’Azur F. Mendivil: Acadia University M. Rocca: Universitá degli Studi dell’Insubria
Keywords
Portfolio optimization ; Stochastic dominance ; Portfolio efficiency ; Partial uncertainty ; Incomplete information ; Set-valued analysis (search for similar items in EconPapers)
Rank
0.74
Search
Portfolio Optimization
Series
Annals of Operations Research 2024 vol. 334 issue 1 No 10 263 pages
Time Added
2024/03/18 03:35
Total Downloads
0
Year Published
2024
TOP