In my recent exploration, I came across this paper on robust portfolio optimization that seems to work well with out of sample situations: Robust portfolio selection problems, by D. Goldfarb G.Iyengar, in Mathematics of Operations Research (2002) corc.ieor.columbia.edu/reports/techreports/tr-2002-03.pdf . Thus, I am wondering what is "state of the art" method, for example, when the price data is realistic with different start date. What are the general methods that are generally considered the best (most robust) in the out of sample context.
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