An artificial intelligence approach to the valuation of American-style derivatives: A use of particle swarm optimization - Ren-Raw Chen; Jeffrey Huang; William Huang; Robert Yu (Journal of Risk and Financial Management, 2021)
In this paper, we evaluate American-style, path-dependent derivatives with an artificial intelligence technique. Specifically, we use swarm intelligence to find the optimal exercise boundary for an American-style derivative. Swarm intelligence is particularly efficient (regarding computation and accuracy) in solving high-dimensional optimization problems and hence, is perfectly suitable for valuing complex American-style derivatives (e.g., multiple-asset, path-dependent) which require a high-dimensional optimal exercise boundary.
Keywords: G12; G13; G4; 330; American option; Monte Carlo; PSO