Bayesian Combinations of Stock Price Predictions with an Application to the Amsterdam Exchange Index
2011-05-02
Research Paper
pp 1-18.
This publication is part of collection
| Related Files |
|---|
View PDF Version
(2011-0824.pdf, 0.1MB) |
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.
Keywords
Classifications using
Journal of Economic Literature (JEL) Classification System
- C15 : Simulation Methods; Monte Carlo Methods; Bootstrap Methods
- E37 : Forecasting and Simulation
- C11 : Bayesian Analysis
- C53 : Forecasting and Other Model Applications
Automatically Extracted Terms
- model
- density
- combination
- forecast
- weight
- prediction
- time t
- stock
- return
- forecasting
- strategy
- scheme
- performance
- fferent
- yt +1
- combination scheme
- investor
- index
- garch
- bayesian
