Proceedings of the 7th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention

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

Authors
Qiang Li, Xueling Zhu
Corresponding Author
Qiang Li
Available Online November 2016.
DOI
https://doi.org/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.
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Proceedings
7th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC-2016)
Part of series
Advances in Intelligent Systems Research
Publication Date
November 2016
ISBN
978-94-6252-242-8
ISSN
1951-6851
DOI
https://doi.org/10.2991/rac-16.2016.81How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

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  - 7th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC-2016)
PB  - Atlantis Press
SP  - 507
EP  - 512
SN  - 1951-6851
UR  - https://doi.org/10.2991/rac-16.2016.81
DO  - https://doi.org/10.2991/rac-16.2016.81
ID  - Li2016/11
ER  -