heteroskedasticity (GARCH) and autoregressive stochastic volatility (ARSV) models for volatility forecasting using the S&P 500 Index. In …-step-ahead volatility forecasts. The empirical results show that the ARSV(1) model outperforms the GARCH(1, 1) model in terms of the in … volatility, are not robust for out-of-sample option price predictions. …

, other continuous time stochastic volatility models that have been proposed, The model generalises the essential features of …

We compare the probabilistic properties of the non-Gaussian Ornstein-Uhlenbeck based stochastic volatility model of … volatility model ; tail behaviour …

Volatility long memory is a stylized fact that has been documented for a long time. Existing literature have two ways … to model volatility long memory: component volatility models and fractionally integrated volatility models. This paper … GARCH(1, 1) model by generating 37% less option pricing errors. With stronger volatility persistence, it also dominates a …

-frequency volatility estimators, market risk evaluation, covariance estimation and multivariate extensions of the processes. The book … and continues to be engaged in research on many topics in finance. His primary areas of interest are volatility, ARCH …