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.
Highlights
Stochastic volatility models are commonly used in the field of mathematical finance and gaining popularity in financial econometrics and management field in particular asset and risk management
We present some preliminaries of important definitions in stochastic volatility
There are significant difference between stochastic volatility has been published with jumps and long memory stochastic volatility in comparison with moment based and simulation based Stochastic Volatility (SV)
Summary
Stochastic volatility models are commonly used in the field of mathematical finance and gaining popularity in financial econometrics and management field in particular asset and risk management. Works by Stein and Stein (1991) and Heston (1993) has improved the Black Scholes model’s assumptions, in which innovations to volatility need not be perfectly correlated with innovations to the price of the underlying asset; and use the stochastic volatility model in their works. Such models can give details for some of the empirical features of the joint time-series behavior of option prices and stock, which cannot be captured by more limited models. The common target of all these authors was to find a new enhanced formula to generalize the Black and Scholes (1973) method to option pricing models with the volatility clustering
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