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 …

trader identifiers at a tick transaction level. Jumps are frequent events and they cluster in time. The order flow imbalance … and the preponderance of aggressive traders, as well as a widening of the bid-ask spread predict them. Jumps have short …

to overestimate the number of jumps in yield spreads and puts the coherence of test results at risk. We formalize the …

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 …