Arbeitspapier

Categorical Forecasts and Non-Categorical Loss Functions

This paper introduces a new test of the predictive performance and market timing for categorical forecasts based on contingency tables when the user has non-categorical loss functions. For example, a user might be interested in the return of an underlying variable instead of just the direction. This new test statistic can also be used to determine whether directional forecasts are derived from non-directional forecasts and whether point forecast have predictive value when transformed into directional forecasts. The tests are applied to the categorical exchange rate forecasts in the ifo-Institute's World Economic Survey and to the point forecasts for quarterly GDP in the Philadelphia Fed's Survey of Professional Forecasters. We find that the loss function matters as exchange rate forecasters perform better under non-categorical loss functions, and the GDP forecasts have value up to two quarters ahead.

Sprache
Englisch

Erschienen in
Series: CESifo Working Paper ; No. 8266

Klassifikation
Wirtschaft
Hypothesis Testing: General
Model Evaluation, Validation, and Selection
Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications
International Finance Forecasting and Simulation: Models and Applications
Thema
contingency tables
categorical forecast
profitability
World Economic Survey
directional accuracy
market timing
forecast value

Ereignis
Geistige Schöpfung
(wer)
Bürgi, Constantin
Boumans, Dorine
Ereignis
Veröffentlichung
(wer)
Center for Economic Studies and ifo Institute (CESifo)
(wo)
Munich
(wann)
2020

Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Bürgi, Constantin
  • Boumans, Dorine
  • Center for Economic Studies and ifo Institute (CESifo)

Entstanden

  • 2020

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