forecasting horizons. Therefore, a long memory volatility model compared to a short memory GARCH model does not appear to improve …

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 …

Motivated by economic-theory concepts - the Fisher hypothesis and the theory of the term structure - we consider a …

reflect information-driven and noise-induced volatilities. We find that all volatility components reveal distinct dynamics and … significantly declines thereafter. Moreover, news-affected responses in all volatility components are influenced by order flow … imbalances. -- efficient return ; macroeconomic announcements ; microstructure noise ; informational volatility …

reflect information-driven and noise-induced volatilities. We find that all volatility components reveal distinct dynamics and … significantly declines thereafter. Moreover, news-affected responses in all volatility components are influenced by order flow … imbalances. -- Efficient Return ; Macroeconomic Announcements ; Microstructure Noise ; Informational Volatility …

volatility processes. This is called a GSSF-SV model. We show that conventional MCMC algorithms for this type of model are …