Abstract
The portfolio selection model proposed by H.Markowitz is a method to manage risk of investment. But there are some criticisms because it is hard to solve the quadratic programming problem when the number of securities to be invested is large. In recent years many fast algorithms have been proposed. In this paper a realistic algorithm to solve Mean-Variance portfolio selection problem is proposed. The idea is originated from the view point of data matrix's rank. This algorithm is an expansion of our previous model to various types of liner constraints. By the algorithm investors can select a portfolio based on their investment policy. In addition to some numerical examples, we discuss the relations of this model to multi-factor model.
