Application of Machine Learning in Option Pricing: A Review

DOI

10.2991/aebmr.k.220405.035How to use a DOI?

Keywords

Machine Learning; Option Pricing; Deep Learning; Neural Network

Abstract

Options occupy a certain position in the derivatives market. Researchers, speculators, and other traders all hope to get a reasonable price for each option. There are only limited options that we can get an accurate solution to the price, and most options we need to get the price numerically. The classical method is poor in processing large data sets and high-dimensional data, and the calculation is slow. With the development of artificial intelligence in recent years, such as machine learning methods, optimization of target values has become easier and easier. So, some scholars, investors and traders began to care the application of artificial intelligence to different kinds of option pricing. This article is a review of the use of different methods in the pricing of different options in the past years and compare the pros and cons of different methods on accuracy and robust.

Copyright

© 2022 The Authors. Published by Atlantis Press International B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license.

Download article (PDF)

TY  - CONF
AU  - Wenda Li
PY  - 2022
DA  - 2022/04/29
TI  - Application of Machine Learning in Option Pricing: A Review
BT  - Proceedings of the 2022 7th International Conference on Social Sciences and Economic Development (ICSSED 2022)
PB  - Atlantis Press
SP  - 209
EP  - 214
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.220405.035
DO  - 10.2991/aebmr.k.220405.035
ID  - Li2022
ER  -