Portfolio selection under distributional uncertainty: A relative robust CVaR approach
作者： Dashan Huang , Shushang Zhu , Frank J. Fabozzi , Masao Fukushima
DOI: 10.1016/J.EJOR.2009.07.010
关键词: Expected shortfall 、 Portfolio 、 Mathematical optimization 、 Optimization problem 、 Robust optimization 、 Rate of return on a portfolio 、 Portfolio optimization 、 Project portfolio management 、 Mathematical economics 、 Economics 、 Post-modern portfolio theory
摘要: Robust optimization, one of the most popular topics in field optimization and control since late 1990s, deals with an problem involving uncertain parameters. In this paper, we consider relative robust conditional value-at-risk portfolio selection where underlying probability distribution return is only known to belong a certain set. Our approach not takes into account worst-case scenarios distribution, but also pays attention best possible decision respect each realization distribution. We illustrate how construct multiple experts (priors) by solving sequence linear programs or second-order cone program.
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