domestic volatility after good shocks but a bad hedge after crashes. …

-parametric regression approach to next-day volatility forecasting. A second finding is that the GARCH(1,1) model severely over-estimated the … unconditional variance leads to poor volatility forecasts during the period under discussion with the MSE of GARCH(1,1) 1-year ahead … volatility more than 4 times bigger than the MSE of a forecast based on historical volatility. We test and reject the hypothesis …

Purpose – The paper seeks to examine changes in daily return volatility associated with open market share repurchases … explore relations between daily return volatility and a number of variables. Findings – This study finds evidence that an open … market share repurchase firm, by actively buying back its shares when the share price falls, reduces daily return volatility …

. Specifically, having modelled the market volatility return like a GARCH (1,1) process and having defined three regimes of … volatility (low, neutral and high), we find that most of the betas in volatility classes are meaningful and positive. We also …

effect on the market return volatility for the period 1999-2005. GARCH and EGARCH models are used to generate variance series … hits and bank returns volatility when it is generated from GARCH model. The price limits policy in ASE does not have their … positive effect in reducing bank return volatility, a result consistent with Chen (1993) and Phylaktis et al. (1999). …

We extend range-based volatility estimation to the multivariate case. In particular, we propose a range …

with a reduction in average annual stock market returns of roughly 2-5%, and a reduction in the volatility of annual stock …