The Mean Squared Prediction Error Paradox: A summary

Pablo Pincheira and Nicolas Hardy

MPRA Paper from University Library of Munich, Germany

Abstract: This is a summary of the paper entitled : “The Mean Squared Prediction Error Paradox”. In that paper, we show that traditional comparisons of Mean Squared Prediction Error (MSPE) between two competing forecasts may be highly controversial. This is so because when some specific conditions of efficiency are not met, the forecast displaying the lowest MSPE will also display the lowest correlation with the target variable. Given that violations of efficiency are usual in the forecasting literature, this opposite behavior in terms of accuracy and correlation with the target variable may be a fairly common empirical finding that we label here as "the MSPE Paradox." We characterize "Paradox zones" in terms of differences in correlation with the target variable and conduct some simple simulations to show that these zones may be non-empty sets. Finally, we illustrate the relevance of the Paradox with two empirical applications.

Keywords: Mean Squared Prediction Error; Correlation; Forecasting; Time Series; Random Walk. (search for similar items in EconPapers)
JEL-codes: C0 C00 C01 C02 C2 C21 C22 C4 C41 C44 C5 C51 C52 C53 C54 C58 E0 E3 E37 E5 E58 E6 F3 F31 F37 F4 F41 F44 F47 G00 G1 G12 G15 G17 (search for similar items in EconPapers)
Date: 2020-12-29
New Economics Papers: this item is included in nep-ecm, nep-for, nep-mac and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:105020

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