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- W1552727409 abstract "In practical portfolio choice models risk is often defined as VaR, expected short-fall, maximum loss, Omega function, etc. and is computed from simulated future scenarios of the portfolio value. It is well known that the minimization of these functions can not, in general, be performed with standard methods. We present a multi-purpose data-driven optimization heuristic capable to deal efficiently with a variety of risk functions and practical constraints on the positions in the portfolio. The efficiency and robustness of the heuristic is illustrated by solving a collection of real world portfolio optimization problems using different risk functions such as VaR, expected shortfall, maximum loss and Omega function with the same algorithm." @default.
- W1552727409 created "2016-06-24" @default.
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- W1552727409 date "2006-01-01" @default.
- W1552727409 modified "2023-10-18" @default.
- W1552727409 title "A Data-Driven Optimization Heuristic for Downside Risk Minimization" @default.
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- W1552727409 doi "https://doi.org/10.2139/ssrn.910233" @default.
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