can generate a plausible disaggregation of the conditional variance process, in which the components' volatility dynamics …

The paper examines the relative performance of Stochastic Volatility (SV) and GARCH(1,1) models fitted to twenty plus … years of daily data for three indices. As a benchmark, I use the realized volatility (RV) for the S&P 500, DOW JONES and … volatility models, if the simple expedient of using lagged squared demeaned daily returns provides a better RV predictor, at …

price volatility. To address this issue, we find a phenomenon, "momentum of jumps" (MoJ), that the predictive ability of the … jump component is persistent when forecasting the oil futures market volatility. Specifically, we propose a strategy that … according to their recent past forecasting performance. The volatility data are based on the intraday prices of West Texas …

The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this … paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility …, which accommodates level shifts, day-of-the-week effects, leverage effects and volatility level effects. Applying the model …

Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these … two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer from … these two family forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the …

Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these … two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer of many … forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the assumptions of jumping …

Rogers-Satchell (RS) measure is an efficient volatility measure. This paper proposes quantile RS (QRS) measure to … on Standard and Poor 500 and Dow Jones Industrial Average indices show that volatility estimates using QRS measures …-of-sample forecast. For return models, the constant mean structure with Student-t errors and QRS volatility estimates provides the best …

We are comparing two approaches for stochastic volatility and jumps estimation in the EUR/USD time series - the non …-parametric power-variation approach using high-frequency returns, and the parametric Bayesian approach (MCMC estimation of SVJD models …) using daily returns. We find that both of the methods do identify continuous stochastic volatility similarly, but they do …

The persistent nature of equity volatility is investigated by means of a multi-factor stochastic volatility model with … model a time-varying generalization of the HAR model for the realized volatility series. It emerges that during the recent … stochastic volatility model suggest that the change in the dynamic structure of the realized volatility during the financial …