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Permanent shocks and forecasting with moving averages

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  • Yoonsuk Lee
  • B. Wade Brorsen

Abstract

Moving averages are a common method of forecasting futures basis. We argue that the optimal lengths of moving averages depend on the frequency of structural breaks. A new stochastic time-series process including structural breaks is modelled by discrete probability distributions that capture the frequency and size of structural breaks. A permanent shock (means structural breaks in this article) is captured by a Poisson-jump or a Bernoulli-jump process, and a temporary shock is represented by a white noise process. Futures basis data are used to estimate the frequency of permanent shocks as well as the size of both shocks. Most shocks are permanent shocks. Since most shocks are permanent, the most recent year provides the best forecast and the optimal length of the moving average is one.

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  • Yoonsuk Lee & B. Wade Brorsen, 2017. "Permanent shocks and forecasting with moving averages," Applied Economics, Taylor & Francis Journals, vol. 49(12), pages 1213-1225, March.
    • Handle: RePEc:taf:applec:v:49:y:2017:i:12:p:1213-1225
    DOI: 10.1080/00036846.2016.1213368
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    2. Joshua G. Maples & B. Wade Brorsen, 2022. "Handling the discontinuity in futures prices when time series modeling of commodity cash and futures prices," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 70(2), pages 139-152, June.

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