frequency information into one model. We consider subsample averaging, bootstrap averaging, forecast averaging methods for the … forecasting the daily S&P 500 index return quantile (Value-at-Risk or VaR is simply the negative of it), using high …-frequency information is beneficial, often substantially and particularly so, in forecasting downside risk. Our empirical results show that …

structure. The book then moves on to non-stationary time series, highlighting its consequences for modeling and forecasting and …1. Introduction -- 2. ARMA models -- 3. Forecasting stationary processes -- 4. Estimation of Mean and Autocovariance … VAR Models -- 13. Forecasting with VAR Models -- 14. Interpretation of VAR Models -- 15. Co-integration -- 16. The Kalman …