Deep backward stochastic differential equation method: Difference between revisions

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==Application==

[[File:Loss function.png|thumb|The dynamically change of loss function|rightup=1.35]]

[[File:Convergence of deep BSDE.jpg|thumb|Convergence of deep BSDE<ref name="Han2018">{{cite journal | last1=Han | first1=J. | last2=Jentzen | first2=A. | last3=E | first3=W. | title=Solving high-dimensional partial differential equations using deep learning | journal=Proceedings of the National Academy of Sciences | volume=115 | issue=34 | pages=8505-8510 | year=2018 }}</ref>]]

Deep BSDE is widely used in the fields of financial derivatives pricing, risk management, and asset allocation. It is particularly suitable for:

# High-Dimensional Option Pricing: Pricing complex derivatives like [[basket options]] and [[Asian options]], which involve multiple underlying assets<ref name="Han2018" />.