We introduce a copula-based dynamic model for multivariate processes of (non-negative) high-frequency trading variables revealing time-varying conditional variances and correlations. Modeling the variables' conditional mean processes using a multiplicative error model we map the resulting...

We propose a new estimator for the spot covariance matrix of a multi-dimensional continuous semi-martingale log asset price process which is subject to noise and non-synchronous observations. The estimator is constructed based on a local average of block-wise parametric spectral covariance...

We model the dynamics of ask and bid curves in a limit order book market using a dynamic semiparametric factor model. The shape of the curves is captured by a factor structure which is estimated nonparametrically. Corresponding factor loadings are assumed to follow multivariate dynamics and are...

The rare disaster hypothesis suggests that the extraordinarily high postwar U.S. equity premium resulted because investors ex ante demanded compensation for unlikely but calamitous risks that they happened not to incur. Although convincing in theory, empirical tests of the rare disaster...

In this paper we develop empirical measures for the strength of spillover effects. Modifying and extending the framework by Diebold and Yilmaz (2011), we quantify spillovers between sovereign credit markets and banks in the euro area. Spillovers are estimated recursively from a vector...

The long-run consumption risk (LRR) model is a promising approach to resolve prominent asset pricing puzzles. The simulated method of moments (SMM) provides a natural framework to estimate its deep parameters, but caveats concern model solubility and weak identification. We propose a twostep...

This paper addresses the open debate about the usefulness of high-frequency (HF) data in large-scale portfolio allocation. Daily covariances are estimated based on HF data of the S&P 500 universe employing a blocked realized kernel estimator. We propose forecasting covariance matrices using a...

We propose a framework for estimating network-driven time-varying systemic risk contributions that is applicable to a high-dimensional financial system. Tail risk dependencies and contributions are estimated based on a penalized two-stage fixed-effects quantile approach, which explicitly links...

Within a two step GARCH framework we estimate the time-varying spillover effects from European and US return innovations to 10 economic sectors within the euro area, the United States, and the United Kingdom. We use daily data from January 1988 - March 2002. At the beginning of our sample...

It is theoretically clear and may be verified empirically that efficient financial markets can make it less necessary for policy to try and offset the welfare effects of labour income risk and unequal consumption dynamics. The literature has also pointed out that, since international competition...