Measure the market risk of the American basket options based on the Least Square Monte Carlo Simulation Approach

DOI

10.2991/rac-16.2016.81How to use a DOI?

Keywords

American basket options;the least Square Mento Carlo simulation;Value at Risk;Latin Hypercubs samping techniques

Abstract

This article applies a simple yet powerful LSM approach for approximating the value of American basket options by simulation.The primary objective is to compare basket Index prices derived from different noise processes. As alternatives,the Brownian motion benchmark is compared to noise processes driven by Gaussian and Student's t copulas, and then three distinct regions of the piecewise distribution is estimated with a semi-parametric probability distribution with generalized Pareto tails. Once we have simulated sample paths, options are priced by the least squares regression method of Longstaff & Schwartz. With the result of American basket put options on stock indices, VaR can be measured by the Latin Hypercubs sampling techniques approximation.The result shows that Latin Hypercubs sampling techniques can be applied to China's stock index option risk measurement.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Qiang Li
AU  - Xueling Zhu
PY  - 2016/11
DA  - 2016/11
TI  - Measure the market risk of the American basket options based on the Least Square Monte Carlo Simulation Approach
BT  - Proceedings of the 7th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention
PB  - Atlantis Press
SP  - 507
EP  - 512
SN  - 1951-6851
UR  - https://doi.org/10.2991/rac-16.2016.81
DO  - 10.2991/rac-16.2016.81
ID  - Li2016/11
ER  -