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Dynamic asset allocation for Pension funds: a model based on genetic algorithms

Ugo Pomante, Vincenzo Farina, Elisa Lupo, Paolo Antonio Cucurachi
March 2023 - n. 3
Keywords: Goal based investing, asset allocation dinamica, algoritmi genetici, asset & liability management, fondi pensione
Jel codes: J26, J32

In this paper we propose a model that, with the help of genetic algorithms, allows the creation of personalized dynamics in the choice of the compartments of a Pension fund, aiming to ensure a high probability of an adequate retirement annuity. Our results confirm the efficiency of the model in converging towards the better solutions in a very limited computing time. This methodology can be easily applied, even in a web-based logic, to define in a personalized way – based on individual pension needs – investment dynamics that can meet social security needs. Its application can help to reduce the pension gap and combat the trend to invest in low-risk sectors, even if the investment time horizons are very long.

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