A Matlab-based rapid method for computing lattice-subspaces and vector sublattices of Rn: Applications in portfolio insurance

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摘要

This paper provides the construction of a powerful and efficient computational method, that translates Polyrakis algorithm [I.A. Polyrakis, Minimal lattice-subspaces, Trans. Am. Math. Soc. 351 (1999) 4183–4203, Theorem 3.19] for the calculation of lattice-subspaces and vector sublattices in Rn. In the theory of finance, lattice-subspaces have been extensively used in order to provide a characterization of market structures in which the cost-minimizing portfolio is price-independent. Specifically, we apply our computational method in order to solve a cost minimization problem that ensures the minimum-cost insured portfolio.

论文关键词:Matlab,Computational methods,Portfolio insurance,Lattice-subspaces,Vector sublattices,Positive basis

论文评审过程:Available online 13 June 2009.

论文官网地址:https://doi.org/10.1016/j.amc.2009.06.018