Exploiting NASDAQ order book data and difference-in-differences methodology, we identify the distinct effects of trading pause mechanisms introduced on U.S. stock exchanges after May 2010. We show that the mere existence of such a regulation constitutes a safeguard which makes market...

We introduce a multivariate multiplicative error model which is driven by componentspecific observation driven dynamics as well as a common latent autoregressive factor. The model is designed to explicitly account for (information driven) common factor dynamics as well as idiosyncratic effects...

1 Introduction -- 2 Microstructure Foundations -- 3 Empirical Properties of High-Frequency Data -- 4 Financial Point Processes -- 5 Univariate Multiplicative Error Models -- 6 Generalized Multiplicative Error Models -- 7 Vector Multiplicative Error Models -- 8 Modelling High-Frequency Volatility...

Bayesian inference is developed and applied for an extended Nelson–Siegel term structure model capturing interest rate risk. The so-called Stochastic Volatility Nelson–Siegel (SVNS) model allows for stochastic volatility in the underlying yield factors. A Markov chain Monte Carlo (MCMC)...