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 …

In this paper, we investigate the dynamic response of stock market volatility to changes in monetary policy. Using a … vector autoregressive model, our findings reveal a significant and asymmetric response of stock returns and volatility to … monetary policy shocks. Although the increase in the volatility risk premium, futures-trading volume, and leverage appear to …

volatility of Borsa Istanbul 100 Index (BIST-100). Sample data cover the period from January 2008 to December 2017. The main … nonlinear volatility models (symmetric and asymmetric Generalized AutoRegressive Conditional Heteroskedasticity [GARCH …]-type models) were used to model and estimate BIST-100 volatility in response to political news. The findings of the paper …

This paper examines the effect of foreign exchange news announcements on the volatility of stock returns in Nigeria … market volatility in Nigeria under symmetric conditional variance. However, there was strong evidence of asymmetric effect … volatility equations. The empirical results revealed a positive and significant effect of exchange news announcements on stock …

The objective of this article is to investigate the volatility asymmetry, volatility-volume relationship by considering …-GARCH models to examine the volatility pattern in the stock market. Second, both contemporaneous and lagged trading volumes are … augmented in the volatility model to empirically verify the validity of Mixture of Distribution Hypothesis (MDH) and Sequential …

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 … two standard volatility models if the simple expedient of using lagged squared demeaned daily returns provides a better RV …

time variation of stock return volatility (GARCH). In the long-term, our results suggest that the US defense firms only …. -- terrorism ; volatility ; GARCH ; event study …

This paper examines long memory volatility in international stock markets. We show that long memory volatility is … memory in volatility than emerging and frontier countries and that stock market jumps are negatively correlated with long … memory of volatility. Overall, our results provide some evidence of a link between stock market uncertainty and macroeconomic …

conditional volatility and strongly support the estimation of dynamic returns that allow for time-varying correlations. A …This study examines the statistical properties required to model the dynamics of both the returns and volatility series … adequately estimate long-memory dynamics in returns and volatility. The in-sample diagnostic tests as well as out …

This article analyzed the presence of long memory in volatility in 5 Asian equity indices namely SENSEX, CNIA, NIKKEI …-sample forecast accuracy. The results confirmed the presence of long memory in both the return and volatility series for all the five … markets under study. Among the group, CNIA and STI showed most persistence in both the return and conditional volatility. In …