study of the volatility as a process of the model parameters. The proof makes use of stochastic recurrence equations for …

in return volatility of Bollerslev and Mikkelsen (1996) by introducing a possible volatility-in-mean effect. To avoid … that the long memory property of volatility carries over to returns, we consider a filtered FIEGARCH-in-mean (FIEGARCH …-M) effect in the return equation. The filtering of the volatility-in-mean component thus allows the co-existence of long memory …

In this paper, I study the drop of real GDP volatility which has been observed in the United States during the postwar …

volatility models including long memory and leverage effects. We compute the price by applying a present value scheme as well as … the Black-Scholes and Hull-White formulas which includes stochastic volatility. We find that long memory as well as …

an approach to model spot prices that combines mean-reversion, spikes and stochastic volatility. Thereby we use different …

Estimation of the volatility of time series has taken off since the introduction of the GARCH and stochastic volatility … models. While variants of the GARCH model are applied in scores of articles, use of the stochastic volatility model is less … unobserved stochastic volatility, and the varying approaches that have been taken for such estimation. In order to simplify the …

We explore the cross-sectional pricing of volatility risk by decomposing equity market volatility into short- and long …-run components. Our finding that prices of risk are negative and significant for both volatility components implies that investors … pay for insurance against increases in volatility, even if those increases have little persistence. The short …