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 …

idiosyncratic jumps, together with conventional long-span asymptotics and Extreme Value Theory (EVT) approximations for consistently … portfolio, we find that the distributions of the systematic and idiosyncratic jumps are both generally heavy-tailed and not … necessarily symmetric. Our estimates also point to the existence of strong dependencies between the market-wide jumps and the …

. Our estimates are based on in-fill asymptotics for directly identifying the jumps, together with Extreme Value Theory (EVT … that the distributions of the systematic and idiosyncratic jumps are both generally heavy-tailed and close to symmetric …

with in-fill asymptotic arguments for uniquely identifying the "large" jumps from the data. The estimation allows for very …

with in-fill asymptotic arguments for uniquely identifying the \large" jumps from the data. The estimation allows for very …

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 …