On the usefulness of cross-validation for directional forecast evaluation

DOI10.1016/J.CSDA.2014.02.001zbMath1506.62022OpenAlexW2006823991MaRDI QIDQ1623514

Y. Aharonov

Publication date: 23 November 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: http://bura.brunel.ac.uk/handle/2438/9833

zbMATH Keywords

linear modelsMonte Carlo analysisblocked cross-validationforecast directional accuracyout-of-sample evaluation

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Linear regression; mixed models (62J05) Applications of statistics to actuarial sciences and financial mathematics (62P05)

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Cites Work

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• Generation Of Time Series Models With Given Spectral Properties
• A survey of cross-validation procedures for model selection
• Consistent cross-validatory model-selection for dependent data: hv-block cross-validation
• Measuring the prediction error. A comparison of cross-validation, bootstrap and covariance penalty methods
• Fast robust estimation of prediction error based on resampling
• Predicting the signs of forecast errors
• Combining forecasts based on multiple encompassing tests in a macroeconomic core system
• Efficient Tests for an Autoregressive Unit Root

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