American Journal of Operations Research

Volume 6, Issue 5 (September 2016)

ISSN Print: 2160-8830   ISSN Online: 2160-8849

Google-based Impact Factor: 1.07  Citations  h5-index & Ranking

Parallel Quasi Exhaustive Search of Optimal Asset Allocation for Pension Funds

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DOI: 10.4236/ajor.2016.65036    1,599 Downloads   2,931 Views  


We present a solution based on a suitable combination of heuristics and parallel processing techniques for finding the best allocation of the financial assets of a pension fund, taking into account all the specific rules of the fund. We compare the values of an objective function computed with respect to a large set (thousands) of possible scenarios for the evolution of the Net Asset Value (NAV) of the share of each asset class in which the financial capital of the fund is invested. Our approach does not depend neither on the model used for the evolution of the NAVs nor on the objective function. In particular, it does not require any linearization or similar approximations of the problem. Although we applied it to a situation in which the number of possible asset classes is limited to few units (six in the specific case), the same approach can be followed also in other cases by grouping asset classes according to their features.

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Bernaschi, M. , Carrozzo, M. , Lulli, M. , Piperno, G. and Vergni, D. (2016) Parallel Quasi Exhaustive Search of Optimal Asset Allocation for Pension Funds. American Journal of Operations Research, 6, 387-400. doi: 10.4236/ajor.2016.65036.

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