Proceedings of the 2022 4th International Conference on Economic Management and Cultural Industry (ICEMCI 2022)

<Previous Article In Volume
Next Article In Volume>

Comparison of Least Square Monte Carlo Algorithm and Binomial Tree Model for Pricing American Options

Authors
Yuxin Meng1, *
1New York University, New York, 10003, United States
*Corresponding author. Email: ym1933@nyu.edu
Corresponding Author
Yuxin Meng
Available Online 27 December 2022.
DOI
10.2991/978-94-6463-098-5_227How to use a DOI?
Keywords
American Options; Least Square Monte Carlo; Binomial Tree; GARCH Model
Abstract

The financial market is a rapidly growing industry where derivatives are popular among investors. The rapid growth of options trading leads to the development of various option pricing theories and models. Through them, Longstaff and Schwartz improved the Monte Carlo model in 2001. The improved least square Monte Carlo simulation (LSM) is widely used in pricing American options. This paper aims to compare two estimation methods in pricing American options, namely the Least Square Monte Carlo Algorithm and the Binomial Tree Model, and detect which model better estimates the accuracy of the operation. In a refinement of using the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model to measure the volatility, an empirical comparison of the models using the Copper future contract is conducted. It is found that the binomial tree method can more accurately predict the American options prediction problem, and applying it to the pricing of copper can not only improve the market but also provide a more reasonable and rapid pricing basis for its subsequent development.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 2022 4th International Conference on Economic Management and Cultural Industry (ICEMCI 2022)
Series
Advances in Economics, Business and Management Research
Publication Date
27 December 2022
ISBN
10.2991/978-94-6463-098-5_227
ISSN
2352-5428
DOI
10.2991/978-94-6463-098-5_227How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Yuxin Meng
PY  - 2022
DA  - 2022/12/27
TI  - Comparison of Least Square Monte Carlo Algorithm and Binomial Tree Model for Pricing American Options
BT  - Proceedings of the 2022 4th International Conference on Economic Management and Cultural Industry (ICEMCI 2022)
PB  - Atlantis Press
SP  - 2019
EP  - 2028
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-098-5_227
DO  - 10.2991/978-94-6463-098-5_227
ID  - Meng2022
ER  -