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Prediction by Exponentially Weighted Moving Averages and Related Methods
Abstract
SUMMARY: The mean square error of prediction is calculated for an exponentially weighted moving average (e.w.m.a.), when the series predicted is a Markov series, or a Markov series with superimposed error. The best choice of damping constant is given; the choice is not critical. There is a value of the Markov correlation ρ 0 below which it is impossible to predict, with an e.w.m.a., the local variations of the series. The mean square error of an e.w.m.a. is compared with the minimum possible value, namely that for the best linear predictor (Wiener). A modified e.w.m.a. is constructed having a mean square error approaching that of the Wiener predictor. This modification will be of value if the Markov correlation parameter is negative, and possibly also when the Markov parameter is near ρ 0.
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Citations
Cited by
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A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series
Marcellino, M., Stock, J. H., & Watson, M. W. (2006) · Journal of Econometrics · doi:10.1016/j.jeconom.2005.07.020 · Cited by 789
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Zheng, J., Xu, C., Zhang, Z., & Li, X. (2017) · 2017 51st Annual Conference on Information Sciences and Systems (CISS) · doi:10.1109/ciss.2017.7926112 · Cited by 341
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Metadata
- Authors
- Cox, D. R.
- Venue
- Journal of the Royal Statistical Society Series B: Statistical Methodology
- Publisher
- Oxford University Press (OUP)
- Published
- 1961-07-01
- Volume
- 23
- Issue
- 2
- Pages
- 414-422
- ISSN
- 1369-7412 (ISSN-L)
- 1467-9868
- OpenAlex
- W105632781
- Cited by
- 263
- References
- 0
- FWCI
- 2.81
- Type
- journal article
- Language
- en
- Open access
- closed
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- Cox, D. R. (1961). Prediction by Exponentially Weighted Moving Averages and Related Methods. Journal of the Royal Statistical Society Series B: Statistical Methodology. https://doi.org/10.1111/j.2517-6161.1961.tb00424.x
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