Summary
With the increasing popularity of defined contribution pension schemes, the related asset allocation problem has become more prominent. The usual portfolio asset allocation approach is far from being appropriate since the asset allocation problem faced by defined contribution pension schemes is fundamentally different. There have been many attempts to solve the problem analytically. However, most of these analytical solutions fail to incorporate real world constraints such as short selling restrictions for the sake of mathematical tractability. In this chapter, we present an evolutionary approach to the asset allocation problem in defined contribution pension schemes. In particular, we compare the simulation results from a genetic algorithm with the results from an analytical model, a simulated annealing algorithm, and two asset allocation strategies that are widely used in practice, namely the life cycle and threshold (funded status) strategies.
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Senel, K., Pamukcu, A.B., Yanik, S. (2008). An Evolutionary Approach to Asset Allocation in Defined Contribution Pension Schemes. In: Brabazon, A., O’Neill, M. (eds) Natural Computing in Computational Finance. Studies in Computational Intelligence, vol 100. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77477-8_3
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DOI: https://doi.org/10.1007/978-3-540-77477-8_3
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