Economic and Statistical Measures of Forecast Accuracy
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Authors
Granger, Clive W. J.
Pesaran, M. Hashem
Publication Date
2004-06-16Series
Cambridge Working Papers in Economics
Publisher
Faculty of Economics
Language
en_GB
Type
Working Paper
Metadata
Show full item recordCitation
Granger, C. W. J., & Pesaran, M. H. (2004). Economic and Statistical Measures of Forecast Accuracy. https://doi.org/10.17863/CAM.5181
Abstract
This paper argues in favour of a closer link between decision and 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 in meteorological forecasts, it is hardly mentioned in standard academic textbooks 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 discussed and useful links between Kuipers score, used as a measure of forecast accuracy in the meteorology literature, and the market timing tests used in finance, are established. An empirical application to the problem of stock market predictability is also provided, and the conditions under which such predictability could be exploited in the presence of transaction costs are discussed.
Keywords
Decision theory, Forecast evaluation, Probabilistsic forecasts, Economic and statistical measures of forecast accuracy, Stock market predictability, Classification-JEL: C12,
Identifiers
This record's DOI: https://doi.org/10.17863/CAM.5181
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