Statistically significant forecasting improvements: how much out-of-sample data is likely necessary? ☆

By Richard A. Ashley. 2003

71 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/15d8a0c6fc1be4d701b9fe86dfe2d33ac5132936

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. G. Zhang

In Finance

1. G. Zhang

In Management Science and Operations Research

1. G. Zhang
2. Lazim Abdullah
3. Durdu Ömer Faruk
4. Mehdi Khashei
5. Mehdi Bijari
6. S. Akar
7. V. Ediger
8. Cornelis W. Oosterlee

Citations in the corpus

• Avoiding Pitfalls in Neural Network Research (2007, background): “Ashley [5] has recently studied the issue of how much out-of-sample data are necessary in order for the forecasting improvement to be statistically significant.”