can lead to different conclusions on the forecasting performance of the MS-GJR model …

Value-at-Risk (VaR) forecasting via a computational Bayesian framework is considered. A range of parametric models are … generalized error distribution. Adaptive Markov chain Monte Carlo methods are employed in estimation and forecasting. A portfolio … of four Asia-Pacific stock markets is considered. Two forecasting periods are evaluated in light of the recent global …

, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to …

In this article, we present a new perspective on forecasting technology adoption, focused on the extensive margin of …

Models based on economic theory have serious problems at forecasting exchange rates better than simple univariate … forecasting. In addition, we adopt a driftless random walk prior, so that cross-dynamics matter for forecasting only if there is … at 1-step ahead. -- Exchange rates ; Forecasting ; Bayesian VAR …