A variety of historical-volatility, peer-historical-volatility, implied-volatility and blended estimators of stock … price volatility are developed and tested for a group of large U.S. companies over roughly a thirty-year window. Longer …-year realized volatility. Inclusion of implied volatility into forecasts at low weightings is found to have little discernible …

This paper examines time-varying stock price and volatility dynamics of constituent industry sector indices in the … of return during rises in aggregate stock market volatility. Finally, this paper identifies which industries exhibit the … highest degree of volatility persistence and how this impacts their respective beta estimates. It shows time-dependence in …

ARFIMA models, as advocated by Jiang and Tian for use in long-term volatility forecasting, are found in a follow …-up empirical study to be dominated by a certain simple historical predictor of stock price volatility at a five-year horizon. (This … volatility, due to bias-related concerns.) A relationship is observed between the estimated fractional-differencing parameter and …

Modeling volatility, or predictable changes over time and space in a variable, is crucial in the natural and social … sciences. Life can be volatile, and anything that matters, and which changes over time and space, involves volatility. Without … volatility, many temporal and spatial variables would simply be constants. Our purpose is to propose a scientific classification …

covariance matrix and the results obtained for the proportion of failure and the dynamic quantile test of Engle and Manganelli … (2004), show evidence in favor of the model of Conditional Constant Correlation …

This paper evaluates the VaR forecasting performance of the Markov regime switching (MRS) based volatility models … volatility models like the EGARCH or GARCH models with a skewed t-student distribution of return innovations can outperform the …

in specific correlation dynamics. A strong implication emerges: during the period under research, and from a different …

time-varying covariance matrix of the multivariate Student's t distribution. The key novelty of our proposed model concerns …