Content analysis of stochastic volatility model in discrete and continuous time setting

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.