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Cluster based portfolio optimization under uncertainty: Statistical and Robust approaches.
Rel. Edoardo Fadda. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Matematica, 2025
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Abstract
Portfolio optimization refers to the process of determining the ideal fraction of an investment capital across a set of assets so that it meets specific requirements or constraints, while aiming for an objective such as minimizing risk or maximizing returns. Often in academic research, this problem is treated as a standalone task, with the portfolio of available securities assumed to be predefined and given as input. In a realistic scenario, the first step towards an optimal allocation is the choice of that portfolio of securities from a set of possible investment opportunities. This thesis aims at studying in detail the two fundamental steps of portfolio management, namely portfolio selection and asset allocation.
The first step is addressed through the application of several clustering algorithms in order to extract useful knowledge from a vast set of investment assets
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