## Abstract Several Bayesian model combination schemes, including some novel approaches that simultaneously allow for parameter uncertainty, model uncertainty and robust timeβvarying model weights, are compared in terms of forecast accuracy and economic gains using financial and macroeconomic time
Economic and statistical measures of forecast accuracy
β Scribed by Clive W. J. Granger; M. Hashem Pesaran
- Publisher
- John Wiley and Sons
- Year
- 2000
- Tongue
- English
- Weight
- 212 KB
- Volume
- 19
- Category
- Article
- ISSN
- 0277-6693
No coin nor oath required. For personal study only.
β¦ Synopsis
This paper argues in favour of a closer link between the decision and the forecast evaluation problems[ Although the idea of using decision theory for forecast evaluation appears early in the dynamic stochastic programming literature\ and has continued to be used with meteorological forecasts\ it is hardly mentioned in standard academic texts on economic forecasting[ Some of the main issues involved are illustrated in the context of a two!state\ two! action decision problem as well as in a more general setting[ Relationships between statistical and economic methods of forecast evaluation are dis! cussed and links between the Kuipers score used as a measure of forecast accuracy in the meteorology literature and the market timing tests used in _nance are established[ An empirical application to the problem of stock market predictability is also provided\ and the conditions under which such predictability could be explained in the presence of transaction costs are discussed [ Copyright Γ 1999 John Wiley
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