900. Cardinality-Constrained Optimization for Large-Scale Portfolio
Invited abstract in session WC-35: Cardinality-constrained optimization with guarantees, stream Continuous and mixed-integer nonlinear programming: theory and algorithms.
Wednesday, 12:30-14:00Room: Michael Sadler LG15
Authors (first author is the speaker)
| 1. | Yuan Chen
|
| Department of Statistics and Operations Research, University of Wien | |
| 2. | Immanuel Bomze
|
| Dept. of Statistics and OR, University of Vienna | |
| 3. | Nikolaus Hautsch
|
| Department of Statistics and Operations Research, University of Vienna | |
| 4. | Bo Peng
|
| University of Southern California |
Abstract
We propose a portfolio optimization model that reconciles Keynes's advocacy for concentrated investments with Markowitz's emphasis on diversification. By incorporating cardinality constraints into the Markowitz mean-variance framework, we enable investors to focus on a small set of assets, fostering specialized expertise. Cardinality constraints allow investors to still use the sample covariance matrix in high-dimensional settings with limited data, balancing diversification needs while mitigating estimation errors inherent in such environments.
Keywords
- Programming, Quadratic
- Programming, Mixed-Integer
- Financial Modelling
Status: accepted
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