A gradient method for high-dimensional BSDEs

Article Properties
  • Language
    English
  • DOI (url)
    10.1515/mcma-2024-2002
  • Publication Date
    2024/02/14
  • Journal
    Monte Carlo Methods and Applications
  • Indian UGC (journal)
  • Refrences
    63
  • Kossi Gnameho Essec, Cergy, France ; and Department of Quantitative Economics , Maastricht University , Maastricht , Netherlands
  • Mitja Stadje Faculty of Mathematics and Economics , University of Ulm , Ulm , Germany
  • Antoon Pelsser Department of Quantitative Economics , Maastricht University , Maastricht , Netherlands
Abstract
Cite
Gnameho, Kossi, et al. “A Gradient Method for High-Dimensional BSDEs”. Monte Carlo Methods and Applications, 2024, https://doi.org/10.1515/mcma-2024-2002.
Gnameho, K., Stadje, M., & Pelsser, A. (2024). A gradient method for high-dimensional BSDEs. Monte Carlo Methods and Applications. https://doi.org/10.1515/mcma-2024-2002
Gnameho K, Stadje M, Pelsser A. A gradient method for high-dimensional BSDEs. Monte Carlo Methods and Applications. 2024;.
Refrences
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  • Science: Mathematics: Probabilities. Mathematical statistics
  • Science: Mathematics
 205 2005
10.1137/05063341X
On discretely reflected backward stochastic differential equations Stochastic Analysis and Applications
  • Technology: Technology (General): Industrial engineering. Management engineering: Applied mathematics. Quantitative methods
  • Science: Mathematics: Probabilities. Mathematical statistics
  • Science: Mathematics
 2 2015
Efficient numerical Fourier methods for coupled forward–backward SDEs Journal of Computational and Applied Mathematics
  • Technology: Technology (General): Industrial engineering. Management engineering: Applied mathematics. Quantitative methods
  • Science: Mathematics
 17 2016
10.1017/S1357321700003913