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 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 …

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 …

It is generally accepted that the asset price processes contain jumps. In fact, pure jump
models have been widely used to model asset prices and/or stochastic volatilities. The …

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

This article develops a new conditional jump model to study jump dynamics in stock market
returns. We propose a simple filter to infer ex post the distribution of jumps. This permits …

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 …

The purpose of this paper is to propose a new class of jump diffusions which feature both
stochastic volatility and random intensity jumps. Previous studies have focused primarily on …

Standard empirical investigations of jump dynamics in returns and volatility are fairly
complicated due to the presence of latent continuous-time factors. We present a new …

This paper examines the joint time series of the S&P 500 index and its options with a two-
factor Hawkes jump-diffusion model that captures jump propagation (ie, the phenomenon in …