  Backwards Stochastic Differential Equations (BSDEs) have been widely employed
in various areas of applied and financial mathematics. In particular, BSDEs
appear extensively in the pricing and hedging of financial derivatives,
stochastic optimal control problems and optimal stopping problems. Most BSDEs
cannot be solved analytically and thus numerical methods must be applied in
order to approximate their solutions. There have been many numerical methods
proposed over the past few decades, for the most part, in a complex and
scattered manner, with each requiring a variety of different and similar
assumptions and conditions. The aim of the present paper is thus to
systematically survey various numerical methods for BSDEs, and in particular,
compare and categorise them. To this end, we focus on the core features of each
method: the main assumptions, the numerical algorithm itself, key convergence
properties and advantages and disadvantages, in order to provide an exhaustive
up-to-date coverage of numerical methods for BSDEs, with insightful summaries
of each and useful comparison and categorization.
