Abstract
We consider the problem of constructing a portfolio of finitely many assets whose returns are described by a discrete joint distribution. We propose mean-risk models that are solvable by linear programming and generate portfolios whose returns are nondominated in the sense of second-order stochastic dominance. Next, we develop a specialized parametric method for recovering the entire mean-risk efficient frontiers of these models and we illustrate its operation on a large data set involving thousands of assets and realizations.
Original language | English (US) |
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Pages (from-to) | 1287-1297 |
Number of pages | 11 |
Journal | Econometrica |
Volume | 71 |
Issue number | 4 |
DOIs |
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State | Published - 2003 |
All Science Journal Classification (ASJC) codes
- Economics and Econometrics
Keywords
- Least absolute deviations
- Linear programming
- Mean-risk analysis
- Parametric simplex method
- Portfolio optimization
- Robust statistics
- Stochastic dominance