This paper uses data from one of the most important European stock markets and shows that, in line with predictions from theoretical market microstructure, a small number of latent factors captures most of the variation in stock specific order books. We show that these order book commonalities...

This paper looks at the interplay of volatility and liquidity on the Euronext trading platform during the December 2, 2002 to April 30, 2003 time period. Using transaction and order book data for some large- and mid-cap Brussels-traded stocks on Euronext, we study the ex-ante liquidity vs...

This paper assesses the possible contemporaneous relationship between stock index prices, earnings and long-term government bond yields for a large number of countries and over a time period that spans several decades. In a cointegration framework, our analysis looks at three hypotheses. First,...

This paper assesses the possible contemporaneous relationship between stock index prices, earnings and long-term government bond yields for a large number of countries and over a time period that spans several decades. In a cointegration framework, our analysis looks at three hypotheses. First,...

Realized covariance models specify the conditional expectation of a realized covariance matrix as a function of past realized covariance matrices through a GARCH-type structure. We compare the forecasting performance of several such models in terms of economic value, measured through economic...

In this paper, we give an overview of the state-of-the-art in the econometric literature on the modeling of so-called financial point processes. The latter are associated with the random arrival of specific financial trading events, such as transactions, quote updates, limit orders or price...

Since the last decade we live in a digitalized world where many actions in human and economic life are monitored. This produces a continuous stream of new, rich and high quality data in the form of panels, repeated cross-sections and long time series . These data resources are available to many...

Adaptive Polar Sampling (APS) is proposed as a Markov chain Monte Carlomethod for Bayesian analysis of models with ill-behaved posteriordistributions. In order to sample efficiently from such a distribution,a location-scale transformation and a transformation to polarcoordinates are used. After...

We model the dynamic volatility and correlation structure of electricity futures of the European Energy Exchange index. We use a new multiplicative dynamic conditional correlation (mDCC) model to separate long-run from short-run components. We allow for smooth changes in the unconditional...

We develop novel multivariate state-space models wherein the latent states evolve on the Stiefel manifold and follow a conditional matrix Langevin distribution. The latent states correspond to time-varying reduced rank parameter matrices, like the loadings in dynamic factor models and the...