10.6084/m9.figshare.1230087.v2
A. S. Hurn
K. A. Lindsay
A. J. McClelland
Estimating the Parameters of Stochastic Volatility Models Using Option Price Data
2015
Taylor & Francis Group
Stochastic Volatility Models
Option Price Data
jump risk premium
volatility model
volatility risk premium
particle filter
Graphics Processing Units
gpu
equity prices
estimation method
period 1990
vanilla options
parameter
likelihood method
jump risk premia
2015-10-27 07:30:35
article
https://tandf.figshare.com/articles/Estimating_the_Parameters_of_Stochastic_Volatility_Models_Using_Option_Price_Data/1230087
<div><p>This article describes a maximum likelihood method for estimating the parameters of the standard square-root stochastic volatility model and a variant of the model that includes jumps in equity prices. The model is fitted to data on the S&P 500 Index and the prices of vanilla options written on the index, for the period 1990 to 2011. The method is able to estimate both the parameters of the physical measure (associated with the index) and the parameters of the risk-neutral measure (associated with the options), including the volatility and jump risk premia. The estimation is implemented using a particle filter whose efficacy is demonstrated under simulation. The computational load of this estimation method, which previously has been prohibitive, is managed by the effective use of parallel computing using graphics processing units (GPUs). The empirical results indicate that the parameters of the models are reliably estimated and consistent with values reported in previous work. In particular, both the volatility risk premium and the jump risk premium are found to be significant.</p></div>