Abstract
Using a closed solution to a Fokker–Planck equation model of a time series, a probability distribution for the next observation is developed. This pdf has one free parameter, b. Various approaches to selecting this parameter have been explored: most recent value, weighted moving average, etc. Here, we explore using a conditional probability distribution for this parameter b, based upon the most recent observation. These methods are tested against some real-world product sales for both a one-step ahead and a two-step ahead forecast. Significant reduction in safety stock levels is found versus an ARMA approach, without a significant increase in out-of-stocks.
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Montagnon, C. (2018). Forecasting via Fokker–Planck Using Conditional Probabilities. In: Rojas, I., Pomares, H., Valenzuela, O. (eds) Time Series Analysis and Forecasting. ITISE 2017. Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-96944-2_1
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DOI: https://doi.org/10.1007/978-3-319-96944-2_1
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