Some New and Efficient Algorithms for Portfolio Analysis.
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WISCONSIN UNIV MADISON MATHEMATICS RESEARCH CENTER
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This paper first describes a modified version of the parametric principal pivoting algorithm for the class of parametric linear complementarity problems with P-matrices. The modified version of the parametric principal pivoting algoritm is then used to develop a new and efficient algorithm to solve the class of portfolio analysis problems with positive definite or equivalently, nonsingular covariance matrices. Extension of the new algorithm to hanlde explicit upper-bounds is also established. The new algorithm and its extension are then specialized to the index models. In these specializations, the algorithms are particularly effective, achieving dramatic savings in both storage and computations. Author
- Statistics and Probability