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    A penalty decomposition algorithm for the extended mean-variance-CVaR portfolio optimization problem

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    Date
    2023
    Author
    Hamdi, A.
    Khodamoradi, T.
    Salahi, M.
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    Abstract
    In this paper, we study mean-variance-Conditional Value-At-Risk (CVaR) portfolio optimization problem with short selling, cardinality constraint and transaction costs. To tackle its mixed-integer quadratic optimization model for large number of scenarios, we take advantage of the penalty decomposition method (PDM). It needs solving a quadratic optimization problem and a mixed-integer linear program at each iteration, where the later one has explicit optimal solution. The convergence of PDM to a partial minimum of original problem is proved. Finally, numerical experiments using the S&P index for 2020 are conducted to evaluate efficiency of the proposed algorithm in terms of return, variance and CVaR gaps and CPU times. 2023 World Scientific Publishing Company.
    DOI/handle
    http://dx.doi.org/10.1142/S1793830923500210
    http://hdl.handle.net/10576/47860
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    • Mathematics, Statistics & Physics [‎790‎ items ]

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