Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
415893 | Computational Statistics & Data Analysis | 2011 | 19 Pages |
Abstract
A portfolio investor requires statistical tools for the timely detection of changes in the optimal portfolio composition. Several multivariate cumulative sum (CUSUM) control charts are proposed for the purpose of monitoring optimal portfolio weights. The ability of the CUSUM schemes to detect important types of changes in the optimal portfolio weights is analyzed in an extensive Monte Carlo simulation study. The empirical application of control charts shows that the proposed methodology can provide a significant reduction of the portfolio volatility.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Vasyl Golosnoy, Sergiy Ragulin, Wolfgang Schmid,