T. Jaditz et Cl. Sayers, OUT-OF-SAMPLE FORECAST PERFORMANCE AS A TEST FOR NONLINEARITY IN TIME-SERIES, Journal of business & economic statistics, 16(1), 1998, pp. 110-117
This article uses a local-information, near-neighbor forecasting metho
dology as a prediction test for evidence of a noisy, chaotic data-gene
rating process underlying the Divisia monetary-aggregate series. Using
a nonparametric method known to perform well with low-dimensional cha
otic processes infected by noise, accompanied by a robust test of fore
cast performance evaluation, we compare out-of-sample forecasting accu
racy from the local-information method to forecasting accuracy from th
e best fitting global linear model. Our results fail to substantiate p
revious claims for determinism in the Divisia monetary-aggregate serie
s because the degree of forecast improvement obtained by the local-inf
ormation method is not consistent with the hypothesis of a low-dimensi
onal attractor underlying the Divisia data.