Choice of Sample Split in Out-of-Sample Forecast Evaluation

By P. R. Hansen, Allan G. Timmermann. 2012

158 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/18ad84849e935022e15548036ce80363fb772e9a

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Citations in the corpus

Testing for Structural Stability of Factor Augmented Forecasting Models (2014, background): “…suggest viewing as a nuisance parameter, which can be integrated out by constructing appropriate summary statistics over a range of values Along the same lines, Hansen and Timmermann (2012) suggest minimizing related statistics over, say, ≤ ≤ The same approach can be followed in our set-up.”
Investor Attention and Stock Returns (2020, unknown): “Rossi and Inoue (2012) and Hansen and Timmermann (2012) show that the out-of-sample tests of”
Time series momentum: Is it there? (2020, unknown): “Hansen and Timmermann (2012) theoretically show that a large K is preferable if the data-generating process is stationary, but it comes at the cost of low power as there are fewer observations for out-of-sample evaluation.”
Out-of-Sample Forecast Tests Robust to the Choice of Window Size (2011, unknown): “Hansen and Timmermann (2012) proposed a sup-type test similar to ours, although they focused on pvalues of the Diebold and Mariano (1995) test statistic estimated via a recursive-window estimation procedure for nested models’ comparisons.”
Forecasting the Equity Risk Premium: The Role of Technical Indicators (2014, unknown): “18 Hansen and Timmermann (2012) show that out-of-sample tests of predictive ability have better size properties when the forecast evaluation period is a relatively large proportion of the available sample, as in our case.”
Advances in Forecasting Under Instability (2012, unknown): “Hansen and Timmermann (2011) consider two interesting empirical analyses.”
Financial credit risk assessment: a recent review (2015, methodology): “In data mining tasks, in-sample is usually used for parameter optimization and model selection, while out-of-sample is used for performance evaluation (Hansen and Timmermann 2012).”