Volume 8, Issue 5, September 2015, Pages 874 - 885
Combining RMT-based filtering with time-stamped resampling for robust portfolio optimization
Authors
David Quintana, Sandra García-Rodríguez, Silvano Cincotti, Pedro Isasi
Corresponding Author
David Quintana
Received 26 October 2014, Accepted 13 June 2015, Available Online 1 September 2015.
- DOI
- 10.1080/18756891.2015.1084707How to use a DOI?
- Keywords
- Portfolio optimization, Filtering, Robustness, Multi-objective optimization
- Abstract
Finding the optimal weights for a set of ï¬nancial assets is a difï¬cult task. The mix of real world constrains and the uncertainty derived from the fact that process is based on estimates for parameters that likely to be inaccurate, often result in poor results. This paper suggests that a combination of a ï¬ltering mechanism based on random matrix theory with time-stamped resampled evolutionary multiobjective optimization algorithms enhances the robustness of forecasted efï¬cient frontiers.
- Copyright
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - David Quintana AU - Sandra García-Rodríguez AU - Silvano Cincotti AU - Pedro Isasi PY - 2015 DA - 2015/09/01 TI - Combining RMT-based filtering with time-stamped resampling for robust portfolio optimization JO - International Journal of Computational Intelligence Systems SP - 874 EP - 885 VL - 8 IS - 5 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2015.1084707 DO - 10.1080/18756891.2015.1084707 ID - Quintana2015 ER -