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

provide a theoretical justification of the use of random subspace methods and show their usefulness when forecasting monthly … randomly weighting the original predictors. Using recent results from random matrix theory, we obtain a tight bound on the mean …

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 …

We present an accurate and efficient method for Bayesian forecasting of two financial risk measures, Value-at-Risk and …

the LISAR model against competing models on synthetic data, showing that LISAR outperforms in forecasting accuracy and … equally good for up to 91% of the time series under consideration in terms of forecasting accuracy. We show in this study … higher accuracy, better forecasting results, and improves the understanding of market movements and sectoral structures. …