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     Research Journal of Applied Sciences, Engineering and Technology


Content Analysis of Stochastic Volatility Model in Discrete and Continuous Time Setting

1, 2Mohammed Al-Hagyan, 2Masnita Misiran and 2Zurni Omar
1Department of Mathematics, Faculty of Science and Human Studies of Aflaj, Sattam Bin Abdulaziz University, Kingdom of Saudi Arabia
2School of Quantitative Sciences, Universiti Utara Malaysia, 06010, Kedah, Malaysia
Research Journal of Applied Sciences, Engineering and Technology  2015  10:1185-1191
http://dx.doi.org/10.19026/rjaset.10.1886  |  © The Author(s) 2015
Received: February ‎22, ‎2015  |  Accepted: March ‎12, ‎2015  |  Published: August 05, 2015

Abstract

This study investigated the popularity of stochastic volatility in recent literature. Stochastic volatility models are common in the financial markets and decision making process. Efficient managing scenarios to these problems will reduce risks in future valuations in many financial assets. A volatility model that is stochastic can better capture the time-varying elements mostly absent in its counterpart, a standard volatility model. In this study, a content analysis is conducted to extract information on mostly used enhancement-stochastic models available in literature. The finding indicates that stochastic volatility with long memory pioneers in SciVerse search engine, whereas stochastic volatility with jump is the highest numbers in publication, in particular the Google Scholar.

Keywords:

Content analysis , stochastic volatility,


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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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