University of GuilanJournal of Mathematical Modeling2345-394X5120170601Robust portfolio selection with polyhedral ambiguous inputs1526200410.22124/jmm.2017.2004ENSomayyehLotfiFaculty of Mathematical Sciences, University of Guilan, Rasht, IranMaziarSalahiFaculty of Mathematical Sciences, University of Guilan, Rasht, IranFarshidMehrdoustFaculty of Mathematical Sciences, University of Guilan, Rasht, IranJournal Article20161226 Ambiguity in the inputs of the models is typical especially in portfolio selection problem where the true distribution of random variables is usually unknown. Here we use robust optimization approach to address the ambiguity in conditional-value-at-risk minimization model. We obtain explicit models of the robust conditional-value-at-risk minimization for polyhedral and correlated polyhedral ambiguity sets of the scenarios. The models are linear programs in the both cases. Using a portfolio of USA stock market, we apply the buy-and-hold strategy to evaluate the model's performance. We found that the robust models have almost the same out-of-sample performance, and outperform the nominal model. However, the robust model with correlated polyhedral results in more conservative solutions.https://jmm.guilan.ac.ir/article_2004_1d74d05dba0e222372683aab00dd663c.pdf