Abstract
The purpose of this paper is to show that an algorithm recently proposed by authors can in fact solve a maximal predictability portfolio (MPP) optimization problem, which is a hard nonconvex fractional programming optimization. Also, we will compare MPP with standard mean-variance portfolio (MVP) and show that MPP outperforms MVP and index. We believe that this paper is of interest to researchers and practitioners in the field of portfolio optimization.
| Original language | English |
|---|---|
| Pages (from-to) | 1095-1109 |
| Number of pages | 15 |
| Journal | International Journal of Theoretical and Applied Finance |
| Volume | 10 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 2007 Sept 1 |
| Externally published | Yes |
Keywords
- 0-1 Integer programming
- Fractional programming
- Global optimization
- Maximal predictability portfolio
- Mean-variance portfolio
- Portfolio optimization
ASJC Scopus subject areas
- Finance
- Economics, Econometrics and Finance(all)