A multivariate positive definite estimator of the integrated covariance matrix of noisy and asynchronously observed asset returns is proposed. We adopt a Bayesian Dynamic Linear Model where microstructure noise is interpreted as measurement error, and asynchronous trading as missing observations...

The analysis of the intraday dynamics of covariances among high-frequency returns is challenging due to asynchronous trading and market microstructure noise. Both effects lead to significant data reduction and may severely affect the estimation of the covariances if traditional methods for...

In this study we provide an analytical characterization of the impact of zero returns on the popular realized covariance estimator of Barndorff-Nielsen and Shephard (2004). In our framework, efficient price processes evolve as a semimartingale with some likelihood of repeated prices. We show...

The estimation of the covariances of high-frequency asset prices is problematic because of asynchronous trading and market microstructure noise. In the last years, both parametric and non-parametric methods have been proposed in order to handle these effects. Little attention has instead been...

We introduce a discrete-time model for log-return dynamics with observable volatility and jumps. Our proposal extends the class of Realized Volatility heterogeneous auto-regressive gamma (HARG) processes adding a jump component with time-varying intensity. The model is able to reproduce the...

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 Exchange, we find that there is a large number of high frequency cojumps. We show that the dynamics of these...