robust estimation of both long-run and short-run volatilities. Our estimation is semiparametric since the long-run volatility … propose different robust estimation methods for nonstationary and strictly stationary GARCH parameters with nonparametric long … run volatility function. Our estimation is based on a two-step LAD procedure. We establish the relevant asymptotic theory …

when estimating error quantiles. In order to prevent this efficiency loss in quantile estimation, we propose a quantile …. At the same time, the efficiency gain in error quantile estimation hinges on the efficiency of estimators of the variance … parameters. We show that the same conclusion applies to the estimation of conditional Expected Shortfall. Our comparison also …

A two-step estimation method of stochastic volatility models is proposed. In the first step, we nonparametrically … estimate the (unobserved) instantaneous volatility process. In the second step, standard estimation methods for fully observed … estimation strategy is applicable to both parametric and nonparametric stochastic volatility models, and can handle both jumps …

nonstationary. We also establish the estimation theory and asymptotic properties for these models in the short horizon and long …

This paper applies a novel bootstrap method, the kernel block bootstrap, to quasi-maximum likelihood estimation of … model illustrates the efficacy of the kernel block bootstrap for quasi-maximum likelihood estimation. …

provide a comprehensive treatment of its use for GMM estimation and inference in time-series models formulated in terms of …

A two-step generalized method of moments estimation procedure can be made robust to heteroskedasticity and …

be stationary and near epoch dependent, the approach in this paper is applicable to estimation and forecasting issues in …