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 …

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 …

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 …

We introduce a statistical test for simultaneous jumps in the price of a financial asset and its volatility process … volatility jumps, we design and analyze a nonparametric spectral estimator of the spot volatility process. A simulation study and … important role played by price volatility co-jumps. …

We estimate a general microstructure model of the transitory and permanent impact of order flow on stock prices. Jumps … microstructure model explains on average 47.7% of the total variation. Once jumps are filtered and parameters are estimated in real …-capitalization stocks traded on the Euronext-Paris Bourse. We find that, at tick frequency, the overnight return, the intraday jumps, and …