Listar Modelos e métodos numéricos en enxeñaría e ciencias aplicadas (M2NICA) por título
Mostrando ítems 25-44 de 95
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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, ... -
Effects of jump-diffusion models for the house price dynamics in the pricing of fixed-rate mortgages, insurance and coinsurance
(Elsevier, 2015)[Abstract] In the pricing of fixed rate mortgages with prepayment and default options, we introduce jump-diffusion models for the house price evolution. These models take into account sudden changes in the price (jumps) ... -
Efficient Calibration and Pricing in LIBOR Market Models with SABR Stochastic Volatility Using GPUs
(Springer, 2016)[Abstract]: In order to overcome the drawbacks of assuming deterministic volatility coefficients in the standard LIBOR market models, several extensions of LIBOR models to incorporate stochastic volatilities have been ... -
End-To-End Multi-Task Learning for Simultaneous Optic Disc and Cup Segmentation and Glaucoma Classification in Eye Fundus Images
(Elsevier, 2022)[Abstract] The automated analysis of eye fundus images is crucial towards facilitating the screening and early diagnosis of glaucoma. Nowadays, there are two common alternatives for the diagnosis of this disease using deep ... -
Enriched finite element subspaces for dual–dual mixed formulations in fluid mechanics and elasticity
(Elsevier, 2005)[Abstract] In this paper we unify the derivation of finite element subspaces guaranteeing unique solvability and stability of the Galerkin schemes for a new class of dual-mixed variational formulations. The approach, which ... -
Equilibrium models with heterogeneous agents under rational expectations and its numerical solution
(Elsevier B.V., 2021-05)[Abstract]: In this work we assume rational expectations to pose general equilibrium models with heterogeneous firms that can enter or exit the industry. More precisely, we assume a general Ito process for the dynamics of ... -
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 ... -
Feedback control of stochastic gene switches using PIDE models
(Elsevier, 2022)[Abstract]: Achieving control of gene regulatory circuits is one of the goals of synthetic biology, as a way to regulate cellular functions for useful purposes (in biomedical, environmental or industrial applications). The ... -
Financial Option Valuation by Unsupervised Learning with Artificial Neural Networks
(MDPI AG, 2020-12-28)[Abstract] Artificial neural networks (ANNs) have recently also been applied to solve partial differential equations (PDEs). The classical problem of pricing European and American financial options, based on the corresponding ... -
First passage times as a measure of hysteresis in stochastic gene regulatory circuits
(Elsevier, 2022)[Abstract]: In the context of phenotype switching and cell fate determination, numerousexperimental studies report hysteresis, despite the fact that the (forward) Chemical Master Equation governing the inherently stochastic ... -
Fully discrete FEM-BEM method for a class of exterior nonlinear parabolic-elliptic problems in 2D
(Elsevier BV * North-Holland, 2006-10)[Abstract] We considered a nonlinear parabolic equation in a bounded domain of R2 coupled with the Laplace equation in the corresponding exterior region. This kind of problems appears in the modelling of quasi-stationary ... -
Global Optimization for Automatic Model Points Selection in Life Insurance Portfolios
(MDPI AG, 2021-02-25)[Abstract] Starting from an original portfolio of life insurance policies, in this article we propose a methodology to select model points portfolios that reproduce the original one, preserving its market risk under a ... -
Global optimization for data assimilation in landslide tsunami models
(Elsevier, 2020-02-15)[Abstract]: The goal of this article is to make automatic data assimilation for a landslide tsunami model, given by the coupling between a non-hydrostatic multi-layer shallow-water and a Savage-Hutter granular landslide ... -
High-order well-balanced numerical schemes for one-dimensional shallow-water systems with Coriolis terms
(Elsevier B.V., 2024-05-15)[Absctract]: The goal of this work is to develop high-order well-balanced schemes for the one-dimensional shallow-water equations with Coriolis terms. The main contribution is the development of general numerical methods ... -
IDESS: a toolbox for identification and automated design of stochastic gene circuits
(Oxford University Press, 2023-11)[Abstract]: Motivation One of the main causes hampering predictability during the model identification and automated design of gene circuits in synthetic biology is the effect of molecular noise. Stochasticity may ... -
IMEX-RK Finite Volume Methods for Nonlinear 1d Parabolic PDEs. Application to Option Pricing
(Springer Nature, 2024-06-06)[Abstract]: The goal of this paper is to develop 2nd order Implicit-Explicit Runge-Kutta (IMEX-RK) finite volume (FV) schemes for solving 1d parabolic PDEs for option pricing, with possible nonlinearities in the source and ... -
Jump-diffusion models with two stochastic factors for pricing swing options in electricity markets with partial-integro differential equations
(Elsevier, 2019)[Abstract] In this paper we consider the valuation of swing options with the possibility of incorporating spikes in the underlying electricity price. This kind of contracts are modelled as path dependent options with ... -
Jump–diffusion productivity models in equilibrium problems with heterogeneous agents
(Elsevier B.V., 2024-11)[Abstract]: In this paper we adopt a rational expectations framework to formulate general equilibrium models with heterogeneous agents. The productivity dynamics are characterized by a jump–diffusion model, thus allowing ... -
Low cost a posteriori error estimators for an augmented mixed FEM in linear elasticity
(Elsevier BV * North-Holland, 2014)[Abstract] We consider an augmented mixed finite element method applied to the linear elasticity problem and derive a posteriori error estimators that are simpler and easier to implement than the ones available in the ... -
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 ...