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Forecasting by splitting a time series using Singular Value Decomposition then using both ARMA and a Fokker Planck equation

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  • Montagnon, C.E.

Abstract

A time series is split into two parts by using Singular Value Decomposition (SVD): one part reflecting the regular effects of exogeneous variables, the other reflecting random effects. The problem of variability of the end points of the constituent series in SVD is resolved. A method is developed of distinguishing the regular part of the series from the random part. The regular part is forecast using ARMA while the random part is forecast based upon a Fokker–Planck equation. This approach is compared to that of a full ARMA forecast on the whole original series.

Suggested Citation

  • Montagnon, C.E., 2021. "Forecasting by splitting a time series using Singular Value Decomposition then using both ARMA and a Fokker Planck equation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    • Handle: RePEc:eee:phsmap:v:567:y:2021:i:c:s0378437120310062
    DOI: 10.1016/j.physa.2020.125708
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