Derivatives Pricing via Machine Learning
40 Pages Posted: 6 Apr 2019 Last revised: 16 Jul 2019
Date Written: April 30, 2019
In this paper, we combine the theory of stochastic process and techniques of machine learning with the regression analysis, first proposed by Longstaff and Schwartz 2001 and apply the new methodologies on financial derivatives pricing. Rigorous convergence proofs are provided for some of the methods we propose. Numerical examples show good applicability of the algorithms.
Keywords: Machine Learning, Regression Analysis, Jump-Diffusion, Derivatives Pricing, Hilbert Space, Orthogonal Projection
JEL Classification: C63
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