Mathematics of Differential Machine Learning in Derivative Pricing and Hedging

arXiv:2405.01233v1 Announce Type: cross
Abstract: This article introduces the groundbreaking concept of the financial differential machine learning algorithm through a rigorous mathematical framework. Diverging from existing literature on financial machine learning, the work highlights the profound implications of theoretical assumptions within financial models on the construction of machine learning algorithms.
This endeavour is particularly timely as the finance landscape witnesses a surge in interest towards data-driven models for the valuation and hedging of derivative products. Notably, the predictive capabilities of …

abstract algorithm algorithms article arxiv assumptions concept construction cs.lg differential financial framework groundbreaking highlights literature machine machine learning machine learning algorithms mathematics pricing q-fin.cp q-fin.mf through type work