leverage effect and maintains a mathematical structure that facilitates volatility estimation. A class of bivariate models that … volatility information improves the day volatility estimation. The results indicate a forecasting improvement using bivariate …We propose a methodology to include night volatility estimates in the day volatility modeling problem with high …

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 …

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 …

breaks) in the volatility of financial time series. Comparative study of three techniques: ICSS, NPCPM and Cheng's algorithm … breaks in volatility, while Cheng's technique works well only when a single break occurs. …

daily realized volatility data of Standard & Poor's 500 (S&P 500) and several other indices, we obtained good performance … heterogeneous autoregressive and other models of realized volatility. …

The paper examines the relative performance of Stochastic Volatility (SV) and Generalised Autoregressive Conditional … Heteroscedasticity (GARCH) (1,1) models fitted to ten years of daily data for FTSE. As a benchmark, we used the realized volatility (RV … standard volatility models if the simple expedient of using lagged squared demeaned daily returns provides a better RV …

market uncertainty and volatility of the investment instruments. Thus, the prediction of the uncertainty and volatilities of … to identify the best fit model that can predict the volatility of return of Bitcoin, which is in high demand as an … the residuals of the average equation model selected have ARCH effect. Volatility of Bitcoin return series after detection …