Portfolio Safeguard (PSG) is a nonlinear and mixed-integer nonlinear optimization package in Windows operating system. PSG contains precoded major classes of nonlinear functions and can optimize these functions in analytic format.
Keywords for this software
References in zbMATH (referenced in 10 articles )
Showing results 1 to 10 of 10.
- Gotoh, Jun-ya; Uryasev, Stan: Two pairs of families of polyhedral norms versus $\ell _p$-norms: proximity and applications in optimization (2016)
- Boyko, Nikita; Karamemis, Gulver; Kuzmenko, Viktor; Uryasev, Stan: Sparse signal reconstruction: LASSO and cardinality approaches (2014)
- Espinoza, Daniel; Moreno, Eduardo: A primal-dual aggregation algorithm for minimizing conditional value-at-risk in linear programs (2014)
- Filomena, Tiago P.; Lejeune, Miguel A.: Warm-start heuristic for stochastic portfolio optimization with fixed and proportional transaction costs (2014)
- Pavlikov, Konstantin; Uryasev, Stan: CVaR norm and applications in optimization (2014)
- Rockafellar, R.T.; Royset, J.O.; Miranda, S.I.: Superquantile regression with applications to buffered reliability, uncertainty quantification, and conditional value-at-risk (2014)
- Tsyurmasto, Peter; Zabarankin, Michael; Uryasev, Stan: Value-at-risk support vector machine: stability to outliers (2014)
- Veremyev, Alexander; Tsyurmasto, Peter; Uryasev, Stan; Rockafellar, R.Tyrrell: Calibrating probability distributions with convex-concave-convex functions: application to CDO pricing (2014)
- Zabarankin, Michael; Uryasev, Stan: Statistical decision problems. Selected concepts and portfolio safeguard case studies (2014)
- Boyko, Nikita; Turko, Timofey; Boginski, Vladimir; Jeffcoat, David E.; Uryasev, Stanislav; Zrazhevsky, Grigoriy; Pardalos, Panos M.: Robust multi-sensor scheduling for multi-site surveillance (2011)