## Abstract This paper considers the forecast accuracy of a wide range of volatility models, with particular emphasis on the use of power transformations. Where oneโperiodโahead forecasts are considered, the power autoregressive models are ranked first by a range of error metrics. Over longer forec
Time series forecasting models involving power transformations
โ Scribed by W. S. Hopwood; J. C. McKeown; P. Newbold
- Publisher
- John Wiley and Sons
- Year
- 1984
- Tongue
- English
- Weight
- 338 KB
- Volume
- 3
- Category
- Article
- ISSN
- 0277-6693
No coin nor oath required. For personal study only.
โฆ Synopsis
In this paper we discuss procedures for overcoming some of the problems involved in fitting autoregressive integrated moving average forecasting models to time series data, when the possibility of incorporating an instantaneous power transformation of the data into the analysis is contemplated. The procedures are illustrated using series of quarterly observations on corporate earnings per share.
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