This paper delineates the simultaneous impact of non-anticipated information on mean and variance of the intraday return process by including appropriate variables accounting for the news flow into both the mean and the variance function. This allows us to differentiate between the consistent...

This paper delineates the simultaneous impact of non-anticipated information on first and second moments of the intraday price process by including appropriate variables accounting for the news flow into both the mean and the variance function. This allows us to differentiate between the...

In this paper, we review the most common specifications of discrete-time stochastic volatility (SV) models and illustrate the major principles of corresponding Markov Chain Monte Carlo (MCMC) based statistical inference. We provide a hands-on ap proach which is easily implemented in empirical...

This paper provides theory as well as empirical results for pre-averaging estimators of the daily quadratic variation of asset prices. We derive jump robust inference for pre-averaging estimators, corresponding feasible central limit theorems and an explicit test on serial dependence in...

We propose a novel approach to model serially dependent positive-valued variables which realize a non-trivial proportion of zero outcomes. This is a typical phenomenon in financial time series observed on high frequencies, such as cumulated trading volumes or the time between potentially...

We propose a novel approach to model serially dependent positive-valued variables which realize a non-trivial proportion of zero outcomes. This is a typical phenomenon in financial time series observed on high frequencies, such as cumulated trading volumes or the time between potentially...