We consider semiparametric estimation of the memory parameter in a modelwhich includes as special cases both the long-memory stochasticvolatility (LMSV) and fractionally integrated exponential GARCH(FIEGARCH) models. Under our general model the logarithms of the squaredreturns can be decomposed...

We establish sufficient conditions on durations that arestationary with finite variance and memory parameter $d \in[0,1/2)$ to ensure that the corresponding counting process $N(t)$satisfies $Var N(t) \sim C t^{2d+1}$ ($Cgt;0$) as $t\rightarrow \infty$, with the same memory parameter $d...

We propose a new semiparametric estimator of the degree of persistence in volatility forlong memory stochastic volatility (LMSV) models. The estimator uses the periodogram ofthe log squared returns in a local Whittle criterion which explicitly accounts for the noise term in the LMSV model....

We propose a new semiparametric estimator of the degree of persistence in volatility forlong memory stochastic volatility (LMSV) models. The estimator uses the periodogram ofthe log squared returns in a local Whittle criterion which explicitly accounts for the noise term in the LMSV model....