We summarize the general combination approach by Billio et al. [2010]. In the combination model the weights follow logistic autoregressive processes, change over time and their dynamics are possible driven by the past forecasting performances of the predictive densities. For illustrative purposes we apply it to combine White Noise and GARCH models to forecast the Amsterdam Exchange index and use the combined predictive forecasts in an investment asset allocation exercise.

density forecast combination, stock data
Bayesian Analysis (jel C11), Simulation Methods; Monte Carlo Methods; Bootstrap Methods (jel C15), Forecasting and Other Model Applications (jel C53), Forecasting and Simulation (jel E37)
Tinbergen Institute
hdl.handle.net/1765/23459
Tinbergen Institute Discussion Paper Series
Discussion paper / Tinbergen Institute
Tinbergen Institute

Billio, M, Casarin, R, Ravazzolo, F, & van Dijk, H.K. (2011). Bayesian Combinations of Stock Price Predictions with an Application to the Amsterdam Exchange Index (No. TI 2011-082/4). Discussion paper / Tinbergen Institute (pp. 1–18). Tinbergen Institute. Retrieved from http://hdl.handle.net/1765/23459