There are occasions when researchers are interested in quarterly forecasts of variables that are released at higher frequencies. In these situations it is common for researchers to convert from the higher frequency to the lower frequency by some method, such as averaging or stock-end, and then to mo
β¦ LIBER β¦
Forecasting monthly and quarterly time series using STL decomposition
β Scribed by Marina Theodosiou
- Book ID
- 113648180
- Publisher
- Elsevier Science
- Year
- 2011
- Tongue
- English
- Weight
- 482 KB
- Volume
- 27
- Category
- Article
- ISSN
- 0169-2070
No coin nor oath required. For personal study only.
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## Abstract The method of ordinary least squares (OLS) and generalizations of it have been the mainstay of most forecasting methodologies for many years. It is wellβknown, however, that outliers or unusual values can have a large influence on leastβsquares estimators. Users of automatic forecasting