the variance matrix. Monte Carlo evidence for parameter estimation based on different small sample sizes is provided. We …

This paper examines the volatility of banks equity weekly returns for six banks (coded B1 to B6) using GARCH models … in Student’s t-distribution are adjudged the best volatility models for B2 and B3 respectively. The study recommends that … in modelling stock market volatility, variants of GARCH models and alternative error distribution should be considered …

increases in realized volatility and arrive when differences-in-opinion among market participants are large at times of FOMC … press releases. Unlike intensity jumps, volatility jumps fail to explain the variation in news-induced realized volatility …

the behaviour of returns and their volatility during both the calm as well as various crises/turmoil periods. Besides the …-GJR-GARCH) were estimated in order to examine the volatility switches of the Central European transition stock markets. The t …-distribution of error terms was used to capture the dynamics of analysed returns more precisely. The results proved high volatility …

Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these … two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer from … these two family forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the …

Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these … two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer of many … forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the assumptions of jumping …