In this paper we investigate the properties of the Lagrange Multiplier [LM] test for autoregressive conditional heteroscedasticity (ARCH) and generalized ARCH (GARCH) in the presence of additive outliers (AOs). We show analytically that both the asymptotic size and power are adversely aected if AOs
Monitoring and adjusting forecasts in the presence of additive outliers
β Scribed by Steven Hillmer
- Publisher
- John Wiley and Sons
- Year
- 1984
- Tongue
- English
- Weight
- 555 KB
- Volume
- 3
- Category
- Article
- ISSN
- 0277-6693
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β¦ Synopsis
The effect of an additive outlier upon the accuracy of forecasts derived from extrapolative methods is investigated. It is demonstrated that an outlier affects not only the accuracy of the forecasts at the time of occurrence but also subsequent forecasts. Methods to adjust for additive outliers are discussed. The results of the paper are illustrated with two examples.
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