A Quantum Computing-based System for Portfolio Optimization using Future Asset Values and Automatic Reduction of the Investment Universe
Eneko Osaba, Guillaume Gelabert, Esther Villar-Rodriguez, Ant\'on Asla, and Izaskun Oregi

TL;DR
This paper introduces Q4FuturePOP, a quantum computing system for portfolio optimization that predicts future asset values and automatically reduces the investment universe to simplify the problem.
Contribution
It presents a novel quantum-based system that incorporates future asset value predictions and automatic universe reduction for improved portfolio optimization.
Findings
Preliminary performance analysis of system modules.
Effective future asset value prediction capabilities.
Automatic universe reduction reduces problem complexity.
Abstract
One of the problems in quantitative finance that has received the most attention is the portfolio optimization problem. Regarding its solving, this problem has been approached using different techniques, with those related to quantum computing being especially prolific in recent years. In this study, we present a system called Quantum Computing-based System for Portfolio Optimization with Future Asset Values and Automatic Universe Reduction (Q4FuturePOP), which deals with the Portfolio Optimization Problem considering the following innovations: i) the developed tool is modeled for working with future prediction of assets, instead of historical values; and ii) Q4FuturePOP includes an automatic universe reduction module, which is conceived to intelligently reduce the complexity of the problem. We also introduce a brief discussion about the preliminary performance of the different modules…
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Taxonomy
TopicsComputational Physics and Python Applications · Financial Markets and Investment Strategies · Complex Systems and Time Series Analysis
