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    Rights statement: The final, definitive version of this article has been published in the Journal, International Journal of Forecasting 31 (1), 2015, © ELSEVIER. DOI#10.1016/j.ijforecast.2014.01.003

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Forecasters and rationality: a comment on Fritsche et al., Forecasting the Brazilian Real and Mexican Peso: Asymmetric loss, forecast rationality and forecaster herding.

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Forecasters and rationality: a comment on Fritsche et al., Forecasting the Brazilian Real and Mexican Peso: Asymmetric loss, forecast rationality and forecaster herding. / Fildes, Robert.
In: International Journal of Forecasting, Vol. 31, No. 1, 01.2015, p. 140-143.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Fildes R. Forecasters and rationality: a comment on Fritsche et al., Forecasting the Brazilian Real and Mexican Peso: Asymmetric loss, forecast rationality and forecaster herding. International Journal of Forecasting. 2015 Jan;31(1):140-143. Epub 2014 Mar 6. doi: 10.1016/j.ijforecast.2014.01.003

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Bibtex

@article{c166f5a08b974c9c85f55a4b57896636,
title = "Forecasters and rationality: a comment on Fritsche et al., Forecasting the Brazilian Real and Mexican Peso: Asymmetric loss, forecast rationality and forecaster herding.",
abstract = "In this commentary stimulated by Fritsche et al.{\textquoteright}s (2014) paper on {\textquoteleft}{\textquoteleft}Forecasting the Brazilian Real and Mexican Peso{\textquoteright}{\textquoteright} and the implications for forecast rationality, I first survey the literature on forecaster behaviour, and conclude that organisational and psychological factors heavily influence the characteristics of the forecasters{\textquoteright} errors in any particular application. Econometric models cannot decompose the error into these potential sources, due to their reliance on non-experimental data. An interdisciplinary research strategy of triangulation is needed if we are to improve both our understanding of forecaster behaviour and the value of such forecasts.",
keywords = "Forecaster behavior, Loss functions, Rationality, Interdiscpinary research",
author = "Robert Fildes",
note = "The final, definitive version of this article has been published in the Journal, International Journal of Forecasting 31 (1), 2015, {\textcopyright} ELSEVIER. DOI#10.1016/j.ijforecast.2014.01.003",
year = "2015",
month = jan,
doi = "10.1016/j.ijforecast.2014.01.003",
language = "English",
volume = "31",
pages = "140--143",
journal = "International Journal of Forecasting",
issn = "0169-2070",
publisher = "Elsevier Science B.V.",
number = "1",

}

RIS

TY - JOUR

T1 - Forecasters and rationality

T2 - a comment on Fritsche et al., Forecasting the Brazilian Real and Mexican Peso: Asymmetric loss, forecast rationality and forecaster herding.

AU - Fildes, Robert

N1 - The final, definitive version of this article has been published in the Journal, International Journal of Forecasting 31 (1), 2015, © ELSEVIER. DOI#10.1016/j.ijforecast.2014.01.003

PY - 2015/1

Y1 - 2015/1

N2 - In this commentary stimulated by Fritsche et al.’s (2014) paper on ‘‘Forecasting the Brazilian Real and Mexican Peso’’ and the implications for forecast rationality, I first survey the literature on forecaster behaviour, and conclude that organisational and psychological factors heavily influence the characteristics of the forecasters’ errors in any particular application. Econometric models cannot decompose the error into these potential sources, due to their reliance on non-experimental data. An interdisciplinary research strategy of triangulation is needed if we are to improve both our understanding of forecaster behaviour and the value of such forecasts.

AB - In this commentary stimulated by Fritsche et al.’s (2014) paper on ‘‘Forecasting the Brazilian Real and Mexican Peso’’ and the implications for forecast rationality, I first survey the literature on forecaster behaviour, and conclude that organisational and psychological factors heavily influence the characteristics of the forecasters’ errors in any particular application. Econometric models cannot decompose the error into these potential sources, due to their reliance on non-experimental data. An interdisciplinary research strategy of triangulation is needed if we are to improve both our understanding of forecaster behaviour and the value of such forecasts.

KW - Forecaster behavior

KW - Loss functions

KW - Rationality

KW - Interdiscpinary research

U2 - 10.1016/j.ijforecast.2014.01.003

DO - 10.1016/j.ijforecast.2014.01.003

M3 - Journal article

VL - 31

SP - 140

EP - 143

JO - International Journal of Forecasting

JF - International Journal of Forecasting

SN - 0169-2070

IS - 1

ER -