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This paper establishes a quadratic unconstrained binary optimization (QUBO) model for portfolio optimization with excess returns. Initially, we decompose the portfolio optimization problem with excess returns and select the QUBO model. Following this, we utilize the iterative quantum annealing algorithm to find the global optimal solution. Lastly, we further discuss the challenges faced in the practical application of the QUBO model. It will not only helps to reveal the potential advantages of the QUBO model in dealing with portfolio optimization problems but also provides references for further research, intending to achieve efficient application in portfolio optimization with excess returns.
Haotian Gu (Tue,) studied this question.