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     Research Journal of Applied Sciences, Engineering and Technology


Modeling the Implied Volatility Surface-: A Study for S&P 500 Index Option

1Jin Zheng and 2Yan Cai
1Department of Mathematical Sciences, University of Liverpool, Liverpool L69 3BX, UK
2Department of Mathematical Sciences, Xi’an Jiaotong University, Shanxi, Xi’an, 430079, China
Research Journal of Applied Sciences, Engineering and Technology  2013  6:1973-1977
http://dx.doi.org/10.19026/rjaset.5.4737  |  © The Author(s) 2013
Received: July 12, 2012  |  Accepted: August 28, 2012  |  Published: February 21, 2013

Abstract

The aim of this study is to demonstrate a framework to model the implied volatilities of S&P 500 index options and estimate the implied volatilities of stock prices using stochastic processes. In this paper, three models are established to estimate whether the implied volatilities are constant during the whole life of options. We mainly concentrate on the Black-Scholes and Dumas’ option models and make the empirical comparisons. By observing the daily-recorded data of S&P 500 index, we study the volatility model and volatility surface. Results from numerical experiments show that the stochastic volatilities are determined by moneyness rather than constant. Our research is of vital importance, especially for forecasting stock market shocks and crises, as one of the applications.

Keywords:

Moneyness, out-of-the money options, parameters estimation, volatility surface,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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