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A Survey on Quantum Computational Finance for Derivatives Pricing and VaR
(Springer, 2022-10)
[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 ...
A Modular Framework for Generic Quantum Algorithms
(MDPI, 2022)
[Abstract] We describe a general-purpose framework to design quantum algorithms. This framework relies on two pillars: a basic data structure called quantum matrix and a modular structure based on three quasi-independent ...
On a Neural Network to Extract Implied Information from American Options
(Routledge, 2022)
[Abstract] Extracting implied information, like volatility and dividend, from observed option prices is a challenging task when dealing with American options, because of the complex-shaped early-exercise regions and the ...
The stochastic θ-SEIHRD model: Adding randomness to the COVID-19 spread
(Elsevier, 2022)
[Abstract]: In this article we mainly extend a newly introduced deterministic model for the COVID-19 disease to a stochastic setting. More precisely, we incorporated randomness in some coefficients by assuming that they ...