We develop a new method that detects jumps nonparametrically in financial time series and significantly outperforms the … generated by a process that experiences both jumps and volatility bursts. As a result, the network learns how to disentangle the …: we obtain fewer spurious detection and identify a larger number of true jumps. When applied to real data, our approach …

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

estimation strategy is applicable to both parametric and nonparametric stochastic volatility models, and can handle both jumps …

noise is considered. A general stochastic volatility framework with jumps for the underlying asset dynamics is defined … parameter and average jumps size reveals that the characteristics of the dataset are crucial to determine which is the proper …