Gómez Tato, AndrésLeitao, ÁlvaroManzano, AlbertoMusso, DanieleNogueiras, María R.Ordóñez, GustavoVázquez, Carlos2023-03-312023-03-312022-10Gómez, A., Leitao, Á., Manzano, A. et al. A Survey on Quantum Computational Finance for Derivatives Pricing and VaR. Arch Computat Methods Eng 29, 4137–4163 (2022). https://doi.org/10.1007/s11831-022-09732-91134-3060http://hdl.handle.net/2183/32821[Abstract]: We review the state of the art and recent advances in quantum computing applied to derivative pricing and the computation of risk estimators like Value at Risk. After a brief description of the financial derivatives, we first review the main models and numerical techniques employed to assess their value and risk on classical computers. We then describe some of the most popular quantum algorithms for pricing and VaR. Finally, we discuss the main remaining challenges for the quantum algorithms to achieve their potential advantages.engAtribución 3.0 Españahttp://creativecommons.org/licenses/by/3.0/es/CostsQuantum computersQuantum theoryValue engineeringjournal articleopen access