Cluster analysis for portfolio optimization
Physics and Society
2008-12-02 v1 Other Condensed Matter
Statistical Finance
Abstract
We consider the problem of the statistical uncertainty of the correlation matrix in the optimization of a financial portfolio. We show that the use of clustering algorithms can improve the reliability of the portfolio in terms of the ratio between predicted and realized risk. Bootstrap analysis indicates that this improvement is obtained in a wide range of the parameters N (number of assets) and T (investment horizon). The predicted and realized risk level and the relative portfolio composition of the selected portfolio for a given value of the portfolio return are also investigated for each considered filtering method.
Keywords
Cite
@article{arxiv.physics/0507006,
title = {Cluster analysis for portfolio optimization},
author = {Vincenzo Tola and Fabrizio Lillo and Mauro Gallegati and Rosario N. Mantegna},
journal= {arXiv preprint arXiv:physics/0507006},
year = {2008}
}
Comments
10 pages, 7 figures