Using a modified DCC-MIDAS specification that allows the long-term correlation component to be a function of multiple … explanatory variables, we show that the stock-bond correlation in the US, the UK, Germany, France, and Italy is mainly driven by … new DCC-MIDAS model, we construct stock-bond hedge portfolios and show that these portfolios outperform various benchmark …

Using a modified DCC-MIDAS specification that allows the long-term correlation component to be a function of multiple … explanatory variables, we show that the stock-bond correlation in the US, the UK, Germany, France, and Italy is mainly driven by …

Modelling and forecasting of asset volatility and covariance is of prime importance in the construction of portfolios … idiosyncratic error terms. We apply this model to forecasting the time-varying covariances in a basket of high interest rate and a …

Multi-Scale Spectral Components model for forecasting high-dimensional covariance matrices based on realized measures …

estimator. We propose forecasting covariance matrices using a multi-scale spectral decomposition where volatilities, correlation … eigenvalues and eigenvectors evolve on different frequencies. In an extensive out-of-sample forecasting study, we show that the …

a blocked realized kernel estimator, different smoothing windows, various regularization methods and two forecasting …

the S&P500 we find that our direct models effectively minimize either statistical or economic forecasting losses both in …

the benchmark (MSCI EFM (World) index) weights. MSCI previously stood for Morgan Stanley Capital International. The …