A Fast Algorithm for Solving Large Scale Mean-variance Models by Compact Factorization of Covariance Matrices
نویسندگان
چکیده
A fast al/lorithm for solving large scale MV (mean-variance) portfolio optimization problems is proposed. It is shown that by using T independent dat.a representing the rate of return of the assets, the MV model consisting of n assets can be put into a quadratic program with n + T variables, T linear const.raints and T quadratic terms in the objective function. As a result, the computation t.ime required to solve this problem would increase very mildly as a function of n. This implies that a very large scale MY model can now be solved in a practical amount of time.
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