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 … limitations. HF data feature microstructure problem, such as the discreteness of the data, the properties of the trading mechanism …

jumps over a grid of thresholds and selects the optimal threshold at what we term the “take-off” point in the estimated … number of jumps. We show that this method consistently estimates the jumps and their indices as the sampling interval goes to … jumps and its ability to distinguish between true jumps and large diffusive moves. In one of these Monte Carlo studies we …

jumps over a grid of thresholds and selects the optimal threshold at what we term the ‘take-off’ point in the estimated … number of jumps. We show that this method consistently estimates the jumps and their indices as the sampling interval goes to … jumps and its ability to distinguish between true jumps and large diffusive moves. In one of these Monte Carlo studies we …

idiosyncratic volatility is notoriously difficult and complex, especially in the presence of jumps, microstructure noise and … methodology is robust to jumps, microstructure noise and asynchronous observation times simultaneously. Analytical bias correction … volatility and realized R-Squared. Because the residual process is latent in the high frequency regression, the estimation of …

value robust volatility estimator with respect to the standard robust volatility estimator as proposed in the paper by … Muneer & Maheswaran (2018b). We show that the robust volatility ratio is unbiased both in the population as well as in finite … samples. We empirically test the robust volatility ratio on 9 global stock indices from America, Asia Pacific and EMEA markets …

assumptions of jumps in prices and leverage effects for volatility. Findings suggest that daily-data models are preferred to HF …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 …

This paper presents a generalized pre-averaging approach for estimating the integrated volatility. This approach also … provides consistent estimators of other powers of volatility in particular, it gives feasible ways to consistently estimate the … asymptotic variance of the estimator of the integrated volatility. We show that our approach, which possess an intuitive …

This paper presents a generalized pre-averaging approach for estimating the integrated volatility. This approach also … provides consistent estimators of other powers of volatility in particular, it gives feasible ways to consistently estimate the … asymptotic variance of the estimator of the integrated volatility. We show that our approach, which possess an intuitive …

This paper presents a generalized pre-averaging approach for estimating the integrated volatility. This approach also … provides consistent estimators of other powers of volatility – in particular, it gives feasible ways to consistently estimate … the asymptotic variance of the estimator of the integrated volatility. We show that our approach, which possess an …

of factor jumps. Such jump dependence is implied by standard linear factor models. Our inference is based on a panel of …