A portfolio investor requires statistical tools for the timely detection of changes in the optimal portfolio composition. Several multivariate cumulative sum (CUSUM) control charts are proposed for the purpose of monitoring optimal portfolio weights. The ability of the CUSUM schemes to detect...

This paper considers estimation of an unknown distribution parameter in situations where we believe that the parameter belongs to a finite interval. We propose for such situations an interval shrinkage approach which combines in a coherent way an unbiased conventional estimator and non-sample...

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...

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...

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...

The dates of the U.S. business cycle are reported by the National Bureau of Economic Research with a considerable delay, so an early notion of turning points is of particular interest. This paper proposes a novel sequential classification approach designed for timely signaling these turning...

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...

A class of dynamic factor and dynamic panel models is proposed for daily high dimensional correlation matrices of asset returns. These flexible semiparametric predictors process ultra high frequency information and allow to exploit both realized correlation matrices and exogenous factors for...

We propose a Conditional Autoregressive Wishart (CAW) model for the analysis of realized covariance matrices of asset returns. Our model assumes an autoregressive moving average structure for the scale matrix of the Wishart distribution. It accounts for positive definiteness of covariance...