GI-M2NICA - Congresos, conferencias, etc.: Envíos recentes
Mostrando ítems 6-10 de 12
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Deep Learning-Based Method for Computing Initial Margin †
(MDPI, 2021)[Abstract] Following the guidelines of the Basel III agreement (2013), large financial institutions are forced to incorporate additional collateral, known as Initial Margin, in their transactions in OTC markets. Currently, ... -
European and American Options Valuation by Unsupervised Learning with Artificial Neural Networks
(MDPI AG, 2020-08-19)[Abstract] Artificial neural networks (ANNs) have recently also been applied to solve partial differential equations (PDEs). In this work, the classical problem of pricing European and American financial options, based ... -
Machine Learning to Compute Implied Volatility from European/American Options Considering Dividend Yield
(MDPI AG, 2020-09-15)[Abstract] Computing implied volatility from observed option prices is a frequent and challenging task in finance, even more in the presence of dividends. In this work, we employ a data-driven machine learning approach ... -
Numerical Simulation of a Nonlinear Problem Arising in Heat Transfer and Magnetostatics
(MDPI AG, 2020-08-19)[Abstract] We present a numerical model that comprises a nonlinear partial differential equation. We apply an adaptive stabilised mixed finite element method based on an a posteriori error indicator derived for this ... -
Computation of Resonance Modes in Open Cavities with Perfectly Matched Layers
(MDPI AG, 2020-08-18)[Abstract] During the last decade, several authors have addressed that the Perfectly Matched Layers (PML) technique can be used not only for the computation of the near-field in time-dependent and time-harmonic scattering ...