We propose a methodology to include night volatility estimates in the day volatility modeling problem with high … the natural relationship between the realized measure and the conditional variance. This improves volatility modeling by … leverage effect and maintains a mathematical structure that facilitates volatility estimation. A class of bivariate models that …

characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in … market volatility, with significant impact on pricing and forecasting of market volatility. The implication is that models … that accomodate long memory hold the promise of improved long-run volatility forecast as well as accurate pricing of long …

-GARCH models to capture time varying volatility and nonlinearity in petrol prices. ANN augmented versions of LSTAR-LST-GARCH models … models, except for the MLP-FIGARCH and MLP-FIAPGARCH models. iv. Volatility clustering, asymmetry and nonlinearity …

We examine the performance of volatility models that incorporate features such as long (short) memory, regime …-t). Second, we perform a comprehensive panel forecasting analysis of the MSM models as well as other competing volatility models … over the alternative volatility models in terms of mean absolute forecast errors and that (iii) forecast combinations …

volatility índices (namely the originally created RTSVX and the new RVI that has replaced it), using daily data over the period …

Even though volatility spillover effects in global equity markets have been documented extensively, the transmission of … illiquidity. We empirically study the illiquidity and volatility spillover effects in eight developed equity markets during and … after the recent financial crisis. The results indicate that equity markets are interdependent, both in terms of volatility …

The transmission mechanisms of volatility between markets can be characterized within a new Markov Switching bivariate …