The main contribution of the paper is to unveil the role of the network structure in the financial markets to improve the portfolio selection process, where nodes indicate securities and edges capture the dependence structure of the system. Three different methods are proposed in order to extract the dependence structure between assets in a network context. Starting from this modified structure, we formulate and then we solve the asset allocation problem. We find that the optimal portfolios obtained through a network-based approach are composed mainly of peripheral assets, which are poorly connected with the others. These portfolios, in the majority of cases, are characterized by an higher trade-off between performance and risk with respect to the traditional global minimum variance portfolio. Additionally, this methodology benefits of a graphical visualization of the selected portfolio directly over the graphic layout of the network, which helps in improving our understanding of the optimal strategy.

Clemente, G., Grassi, R., Hitaj, A. (2021). Asset allocation: new evidence through network approaches. ANNALS OF OPERATIONS RESEARCH, 299(1-2), 61-80 [10.1007/s10479-019-03136-y].

Asset allocation: new evidence through network approaches

Grassi, Rosanna;Hitaj, Asmerilda
2021

Abstract

The main contribution of the paper is to unveil the role of the network structure in the financial markets to improve the portfolio selection process, where nodes indicate securities and edges capture the dependence structure of the system. Three different methods are proposed in order to extract the dependence structure between assets in a network context. Starting from this modified structure, we formulate and then we solve the asset allocation problem. We find that the optimal portfolios obtained through a network-based approach are composed mainly of peripheral assets, which are poorly connected with the others. These portfolios, in the majority of cases, are characterized by an higher trade-off between performance and risk with respect to the traditional global minimum variance portfolio. Additionally, this methodology benefits of a graphical visualization of the selected portfolio directly over the graphic layout of the network, which helps in improving our understanding of the optimal strategy.
Articolo in rivista - Articolo scientifico
Dependence structure; Global minimum variance; Networks; Portfolio selection;
English
11-gen-2019
2021
299
1-2
61
80
reserved
Clemente, G., Grassi, R., Hitaj, A. (2021). Asset allocation: new evidence through network approaches. ANNALS OF OPERATIONS RESEARCH, 299(1-2), 61-80 [10.1007/s10479-019-03136-y].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/214568
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