Download This PaperAn Artificial Intelligence Approach to the Valuation of American-style Derivatives: A Use of Particle Swarm Optimization
37 Pages Posted: 30 Sep 2020
Date Written: August 14, 2020
Abstract
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 (computation and accuracy) in solving high-dimensional optimization problems and hence perfectly suitable for valuing complex American-style derivatives (e.g. multiple-asset, path-dependent) which require a high-dimensional optimal exercise boundary.
Keywords: American Option, Monte Carlo, PSO
JEL Classification: G12, G13, G4
Suggested Citation: Suggested Citation
Chen, Ren-Raw, An Artificial Intelligence Approach to the Valuation of American-style Derivatives: A Use of Particle Swarm Optimization (August 14, 2020). Available at SSRN: https://ssrn.com/abstract=3673898 or http://dx.doi.org/10.2139/ssrn.3673898
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