This study reconsiders the role of jumps for volatility forecasting by showing that jumps have a positive and mostly … significant impact on future volatility. This result becomes apparent once volatility is separated into its continuous and … yields) shows that the proposed techniques improve significantly the accuracy of volatility forecasts especially in periods …

"low" and "high" volatility periods. These periods are determined by estimating asset dynamics using a SWARCH process. Our … results suggest that securities volatility is higher during periods of financial or economic instability. We use these results … to evaluate the impact of news during "low" and "high" volatility periods using a GARCH model. News effects, especially …

The present study is an attempt to investigate the conditional volatility of returns of the two major segments of …) prices. For studying the spill-over of volatility from a market to another, squared residuals (after standardization) from … presence of conditional volatility of returns. The optimal model was identified as ARCH (1) when Re/$ Exchange Rate was the …

volatility index (VIX) via a nonparametric copula method. Specifically, we propose a conditional dependence index to investigate … that the nonparametric leverage effect is much stronger than the nonparametric volatility feedback effect, although, in …

return and volatility spillover between the S&P 500 and 12 Asian stock markets using weekly data from January 2000 to … February 2020. DECO-GARCH models are employed to measure volatility transmission between markets. A generalized VAR, variance … the interdependence of the conditional returns, conditional volatility, and conditional correlations between the stock …