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Deep backward stochastic differential equation method
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<p>Deep backward stochastic differential equation method is a numerical method that combines <a href="/facts/Deep_learning/JLuwD3ea">deep learning</a> with <a href="/facts/Backward_stochastic_differential_equation/cIpkLhaY">Backward stochastic differential equation</a> (BSDE). This method is particularly useful for solving high-dimensional problems in <a href="/facts/Financial_derivatives/jx4CbakW">financial derivatives</a> pricing and <a href="/facts/Risk_management/xGhxtxdp">risk management</a>. By leveraging the powerful function approximation capabilities of <a href="/facts/Deep_neural_networks/JLuwD3ea">deep neural networks</a>, deep BSDE addresses the computational challenges faced by traditional numerical methods in high-dimensional settings. </p>