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[01309] Deep Learning Methods for BSDEs/PDEs in Finance

  • Session Time & Room : 4E (Aug.24, 17:40-19:20) @E506
  • Type : Contributed Talk
  • Abstract : In this work we present both a multistep deep learning method with automatic differentiation for the resolution of nonlinear PDEs and BSDEs and an adaptation of the Deep BSDE method for Quadratic BSDE and HJB equations. An approximation error result and error rate is proved for the schemes when using a class of networks with sparse weights. Applications to finance including CVA, portfolio optimisation under exponential utility and options pricing will be presented.
  • Classification : 65Cxx, 65Nxx, 60Hxx, 91Gxx, 68T07
  • Format : Talk at Waseda University
  • Author(s) :
    • Daniel Bussell (UCL)