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

C.E. Montagnon

Physica A: Statistical Mechanics and its Applications, 2021, vol. 567, issue C

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.

Keywords: Forecasting; Time-series; Splitting; SVD; ARMA; Fokker–Planck (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:567:y:2021:i:c:s0378437120310062

DOI: 10.1016/j.physa.2020.125708

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