The approach we present is based on Artificial Neural Networks (ANNs) which previously have been successfully applied in many contexts such as Image recognition and Natural Language Processing.
The first article in this series contained a high-level introduction to ANNs and this second article builds on that to describe how such networks can be used as a substitute to the more established methods when exposed to a problem that requires nested simulations. We specifically address what to consider when calibrating the model and how to approach the training process.
Part II - Artificial Neural Networks as a Substitute to LSMC and Nested Simulations
In this article series we present a machine learning-based approach to solving a common problem in financial modelling where one is faced with the task of estimating the value of a function which requires a significant amount of computation to evaluate. More specifically a function that corresponds to a so called nested simulation aimed at for example estimating a capital requirement for a financial institution or the risk associated with a structured product for a retail investor.
2021-01-22
