forecasting horizons. Therefore, a long memory volatility model compared to a short memory GARCH model does not appear to improve …

Alternative strategies for predicting stock market volatility are examined. In out-of-sample forecasting experiments … implied-volatility information, derived from contemporaneously observed option prices or history-based volatility predictors …, such as GARCH models, are investigated, to determine if they are more appropriate for predicting future return volatility …

characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in … market volatility, with significant impact on pricing and forecasting of market volatility. The implication is that models … that accomodate long memory hold the promise of improved long-run volatility forecast as well as accurate pricing of long …

characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in … market volatility, with significant impact on pricing and forecasting of market volatility. The implication is that models … that accomodate long memory hold the promise of improved long-run volatility forecast as well as accurate pricing of long …

past domestic volatilities does not generally affect the mean and the volatility of the estimated thresholds. Specifically …, with the exception of the Italian market we find at least two volatility regimes, due to an asymmetric structure of … volatility as a function of bad and good domestic news. Moreover, in the majority of the series under scrutiny we also identify …