We explore a new approach to the forecasting of macroeconomic variables based on a dynamic factor state space analysis … forecasting purposes. Given a dynamic factor model as the data generation process, we provide Monte Carlo evidence for the finite … unbalanced panel contain quarterly and monthly variables. The forecasting accuracy is measured against a set of benchmark models …

We explore a new approach to the forecasting of macroeconomic variables based on a dynamic factor state space analysis … forecasting purposes. Given a dynamic factor model as the data generation process, we provide Monte Carlo evidence for the finite … unbalanced panel contain quarterly and monthly variables. The forecasting accuracy is measured against a set of benchmark models …

returns and intradaily squared returns for forecasting horizons rangingfrom 1 to 10 days. For the daily squared returns we …

wholesale power markets have only recently been deregulated. We introduce the weather factor into well-known forecasting models …

forecasting the term structure of interest rates. As expected, I find that using more flexible models leads to a better in …

explores various specifications of decompositions and various forecasting experiments. The result from these horse-races is … for richer forecasting specifications, the paper shows, using Bayesian model averaging techniques (BMA), that the …

underwriters and issuing firms in the Japanese corporate bond market, stochastic life table forecasting: a time-simultaneous fan …

of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting …

Many economic studies on inflation forecasting have found favorable results when inflation is modeled as a stationary … process around a slowly time-varying trend. In contrast, the existing studies on interest rate forecasting either treat yields … the problem of forecasting the term structure of interest rates with the assumption that the yield curve is driven by …