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 …

and explanatory variables. The latent factors are modelled by stochastic processes. The idiosyncratic disturbances are … procedures for the estimation of the factors and parameter estimation by maximum likelihood and Bayesian methods. An illustration …

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

under the Basel Accord: A Bayesian approach to forecasting value-at-risk of VIX futures, fast clustering of GARCH processes … dynamics of BRICS's country risk ratings and domestic stock markets, U.S. stock market and oil price, forecasting value …

construction methods, we find that this procedure leads to better interpretable factors and to a favorable forecasting performance … number of representative factors. We propose a novel factor construction procedure that enjoys the properties of robustness …

provide a theoretical justification of the use of random subspace methods and show their usefulness when forecasting monthly …

For forecasting volatility of futures returns, the paper proposes an indirect method based on the relationship between … futures and the underlying asset for the returns and time-varying volatility. For volatility forecasting, the paper considers … that the new method based on stochastic volatility models with the asymmetry and long memory outperforms the forecasting …

forecasting occur much less frequently than indicated by existing tests. …