Name
Abstract | ||
|---|---|---|
This paper proposes an asymmetric approximation method for the chance-constrained portfolio selection model based on robust optimization techniques. We choose 30 assets from Chinese market to construct a portfolio and compare the performance of our model with Gauss approximation and Chebyshev approximation models. The experimental study shows that our model is able to put more weight on stocks with higher returns. Since, there is short-run persistence of the relative performance of the stocks, the portfolios constructed by our model can produce higher cumulative portfolio returns in the near future. (C) 2017 The Authors. Published by Elsevier B.V. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.procs.2017.11.491 | 5TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND QUANTITATIVE MANAGEMENT, ITQM 2017 |
Keywords | Field | DocType |
chance constraint, portfolio selection, robust optimization, asymmetry | Econometrics,Gauss,Computer science,Robust optimization,Approximation theory,Portfolio,Artificial intelligence,Stock (geology),Empirical research,Machine learning | Conference |
Volume | ISSN | Citations |
122 | 1877-0509 | 0 |
PageRank | References | Authors |
0.34 | 4 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yingwei Han | 1 | 0 | 0.34 |
| Ping Li | 2 | 78 | 14.22 |