Abstract
In this paper we briefly review two recent use-cases of quantum optimization algorithms applied to hard problems in finance and economy. Specifically, we discuss the prediction of financial crashes as well as dynamic portfolio optimization. We comment on the different types of quantum strategies to carry on these optimizations, such as those based on quantum annealers, universal gate-based quantum processors, and quantum-inspired Tensor Networks.
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Acknowledgements
Thanks to Christophe Jurczak, Pedro Luis Uriarte, Pedro Muñoz-Baroja, Creative Destruction Lab, BIC-Gipuzkoa, DIPC, Ikerbasque, and Basque Government for constant support. We extend special thanks to our collaborators Francesco Benfenati, Beñat Mencia Uranga, and Samuel Palmer, for stimulating discussions and interesting ideas.
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Mugel, S., Lizaso, E., Orús, R. (2022). Use Cases of Quantum Optimization for Finance. In: Sriboonchitta, S., Kreinovich, V., Yamaka, W. (eds) Credible Asset Allocation, Optimal Transport Methods, and Related Topics. TES 2022. Studies in Systems, Decision and Control, vol 429. Springer, Cham. https://doi.org/10.1007/978-3-030-97273-8_15
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