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Fast Bayesian Calibration of Option Pricing Models Based on Sequential Monte Carlo Methods and Deep Learning.

Model calibration is a challenging yet fundamental task in financial engineering. Using sequential Monte Carlo methods, we reformulate the nonconvex optimization problem as a Bayesian estimation task. This allows to compute any statistic of the estimated parameters, mitigating the strong dependence...

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Publicado en:Journal of Financial Econometrics Vol. 24; no. 3; pp. 1 - 25
Autores principales: Brignone, Riccardo, Gonzato, Luca, Knaust, Sven, Lütkebohmert, Eva
Formato: Artículo
Publicado: Oxford University Press / USA 2026
Materias:
Monte Carlo method
Bayes' estimation
Standard & Poor's 500 Index
Markov chain Monte Carlo
Financial engineering
Deep learning
Artificial neural networks
Acceso en línea:Ver este registro en EBSCOhost