The simultaneous occurrence of jumps in several stocks can be associated with major financial news, triggers short …

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 …

While attention is a predictor for digital asset prices, and jumps in Bitcoin prices are well-known, we know little … digital asset returns are driven by high frequency jumps clustered around black swan events, resembling volatility and trading … volume seasonalities. Regressions show that intra-day jumps significantly influence end of day returns in size and direction …

of asset prices. We derive jump robust inference for pre-averaging estimators, corresponding feasible central limit … interval length. Moreover, we investigate the dependence of pre-averaging based inference on the sampling scheme, the sampling … frequency, microstructure noise properties as well as the occurrence of jumps. As a result of a detailed empirical study we …