Testing Density Forecasts, With Applications to Risk Management
| Autor: | Jeremy Berkowitz |
|---|---|
| Rok vydání: | 2001 |
| Předmět: |
Statistics and Probability
Economics and Econometrics business.industry Financial risk Forecast skill Forecast verification Sample size determination Economics Econometrics Statistics Probability and Uncertainty Single point Consensus forecast Point forecast business Social Sciences (miscellaneous) Risk management |
| Zdroj: | Journal of Business & Economic Statistics. 19:465-474 |
| ISSN: | 1537-2707 0735-0015 |
| DOI: | 10.1198/07350010152596718 |
| Popis: | The forecast evaluation literature has traditionally focused on methods of assessing point forecasts. However, in the context of many models of financial risk, interest centers on more than just a single point of the forecast distribution. For example, value-at-risk models that are currently in extremely wide use form interval forecasts. Many other important financial calculations also involve estimates not summarized by a point forecast. Although some techniques are currently available for assessing interval and density forecasts, existing methods tend to display low power in sample sizes typically available. This article suggests a new approach to evaluating such forecasts. It requires evaluation of the entire forecast distribution, rather than a scalar or interval. The information content of forecast distributions combined with ex post realizations is enough to construct a powerful test even with sample sizes as small as 100. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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