Computing near-optimal Value-at-Risk portfolios using integer programming techniques

@article{Babat2018ComputingNV,
  title={Computing near-optimal Value-at-Risk portfolios using integer programming techniques},
  author={Onur Babat and Juan C. Vera and Luis Fernando Zuluaga},
  journal={Eur. J. Oper. Res.},
  year={2018},
  volume={266},
  pages={304-315}
}
Value-at-Risk (VaR) is one of the main regulatory tools used for risk management purposes. However, it is difficult to compute optimal VaR portfolios; that is, an optimal risk-reward portfolio allocation using VaR as the risk measure. This is due to VaR being non-convex and of combinatorial nature. In particular, it is well-known that the VaR portfolio problem can be formulated as a mixed-integer linear program (MILP) that is difficult to solve with current MILP solvers for medium to large… Expand

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