We examine the clustering behavior of price and variance jumps using high-frequency data,
modeled as a marked Hawkes process (MHP) embedded in a bivariate jump-diffusion …

Dynamic jumps in the price and volatility of an asset are modelled using a joint Hawkes
process in conjunction with a bivariate jump diffusion. A state‐space representation is used …

We study the bivariate jump process involving the S&P 500 and the Euro Stoxx 50, with
jumps extracted from high-frequency data. In our analysis, based on Hawkes processes, we …

Instabilities in the price dynamics of a large number of financial assets are a clear sign of
systemic events. By investigating a set of 20 high cap stocks traded at the Italian Stock …

We are comparing two approaches for stochastic volatility and jumps estimation in the
EUR/USD time series-the non-parametric power-variation approach using high-frequency …

Instabilities in the price dynamics of a large number of financial assets are a clear sign of
systemic events. By investigating portfolios of highly liquid stocks, we find that there are a …

Hawkes processes have been finding more applications in diverse areas of science,
engineering and quantitative finance. In multi-frequency finance various phenomena have …

We introduce a novel stochastic volatility model with price and volatility co-jumps driven by
Hawkes processes and develop a feasible maximum-likelihood procedure to estimate the …

We study the clustering behavior of stock return jumps modeled by a self/cross-exciting
process embedded in a stochastic volatility model. Based on the model estimates, we …

This paper is concerned with the statistical modelling of the high-frequency dynamics of
financial markets. We study whether a systemic component in a multi-asset price model can …