Derivatives Pricing via Machine Learning

40 Pages Posted: 6 Apr 2019 Last revised: 16 Jul 2019

See all articles by Tingting Ye

Tingting Ye

Boston University - Questrom School of Business

Liangliang Zhang

Dongxing Securities

Date Written: April 30, 2019

Abstract

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

Suggested Citation

Ye, Tingting and Zhang, Liangliang, Derivatives Pricing via Machine Learning (April 30, 2019). Boston University Questrom School of Business Research Paper No. 3352688, Available at SSRN: https://ssrn.com/abstract=3352688 or http://dx.doi.org/10.2139/ssrn.3352688

Tingting Ye

Boston University - Questrom School of Business ( email )

595 Commonwealth Avenue
Boston, MA MA 02215
United States

Liangliang Zhang (Contact Author)

Dongxing Securities ( email )

Yangshupu Rd. No. 248
Hongkou District
Shanghai, Shanghai 200433
China

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