Random Matrix Filtering in Portfolio Optimization
Physics and Society
2008-12-02 v1 Statistical Finance
Abstract
We study empirical covariance matrices in finance. Due to the limited amount of available input information, these objects incorporate a huge amount of noise, so their naive use in optimization procedures, such as portfolio selection, may be misleading. In this paper we investigate a recently introduced filtering procedure, and demonstrate the applicability of this method in a controlled, simulation environment.
Cite
@article{arxiv.physics/0509235,
title = {Random Matrix Filtering in Portfolio Optimization},
author = {Gabor Papp and Szilard Pafka and Maciej A. Nowak and Imre Kondor},
journal= {arXiv preprint arXiv:physics/0509235},
year = {2008}
}
Comments
9 pages with 3 EPS figures