We consider the problem of ex-ante forecasting conditional correlation patterns using ultra high frequency data. Flexible semiparametric predictors referring to the class of dynamic panel and dynamic factor models are adopted for daily forecasts. The parsimonious set up of our approach allows to...

Using a novel four-phase model based upon a conditional autoregressive Wishart framework for realized variances and covariances we quantify intra-daily volatility spillovers within and across the US, German and Japanese stock markets before and during the subprime crisis. We find significant...

In this paper we model the dynamics of 100 years long monthly price series of eight non-ferrous and precious metals. Applying the state space framework we impose and identify two common factors related to non-ferrous and precious metals, respectively, which exhibit quite distinct autoregressive...

In this paper we adapt the empirical similarity (ES) concept for the purpose of combining volatility forecasts originating from different models. Our ES approach is suitable for situations where a decision maker refrains from evaluating success probabilities of forecasting models but prefers to...

Using a novel three-phase model based upon a conditional autoregressive Wishart (CAW) framework for the realized (co)variances of the US Dow Jones and the German stock index DAX, we analyze intra-daily volatility spillovers between the US and German stock markets. The proposed model explicitly...

This paper elaborates sequential procedures for monitoring the validity of a volatility model. A state-space representation describes dynamics of daily integrated volatility. The observation equation relates the integrated volatility to its measures such as the realized volatility or bipower...

The dates of U.S. business cycle are reported by NBER with a considerable delay, so an early notion of turning points is of particular interest. This paper proposes a novel sequential approach designed for timely signaling these turning points. A directional cumulated sum decision rule is...

We propose a Conditional Autoregressive Wishart (CAW) model for the analysis of realized covariance matrices of asset returns. Our model assumes a generalized linear autoregressive moving average structure for the scale matrix of the Wishart distribution allowing to accommodate for complex...