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One of the problems in quantitative finance that has received the mostattention is the portfolio optimization problem. Regarding its solving, thisproblem has been approached using different techniques, with those related toquantum computing being especially prolific in recent years. In this study, wepresent a system called Quantum Computing-based System for PortfolioOptimization with Future Asset Values and Automatic Universe Reduction(Q4FuturePOP), which deals with the Portfolio Optimization Problem consideringthe following innovations: i) the developed tool is modeled for working withfuture prediction of assets, instead of historical values; and ii) Q4FuturePOPincludes an automatic universe reduction module, which is conceived tointelligently reduce the complexity of the problem. We also introduce a briefdiscussion about the preliminary performance of the different modules thatcompose the prototypical version of Q4FuturePOP.

A Quantum Computing-based System for Portfolio Optimization using Future Asset Values and Automatic Reduction of the Investment Universe