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Lower and upper bounds for strong approximation errors for numerical approximations of stochastic heat equations
(2018)SAM Research ReportReport -
Solving high-dimensional optimal stopping problems using deep learning
(2019)SAM Research ReportNowadays many financial derivatives which are traded on stock and futures exchanges, such as American or Bermudan options, are of early exercise type. Often the pricing of early exercise options gives rise to high-dimensional optimal stopping problems, since the dimension corresponds to the number of underlyings in the associated hedging portfolio. High-dimensional optimal stopping problems are, however, notoriously difficult to solve due ...Report -
Strong convergence rates for explicit space-time discrete numerical approximations of stochastic Allen-Cahn equations
(2017)SAM Research ReportReport -
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Solving stochastic differential equations and Kolmogorov equations by means of deep learning
(2018)Research ReportReport -
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Strong convergence rates for nonlinearity-truncated Euler-type approximations of stochastic Ginzburg-Landau equations
(2016)Research ReportReport