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Joakim Westerlund. Photo.

Joakim Westerlund

Professor, Programme director – Master of Data Analytics and Business Economics

Joakim Westerlund. Photo.

Testing for predictability in panels of any time series dimension

Author

  • Joakim Westerlund
  • Paresh Narayan

Summary, in English

The few panel data tests for predictability of returns that exist are based on the prerequisite that both the number of time series observations, $T$, and the number of cross-section units, $N$, are large. As a result, these tests are impossible for stock markets where lengthy time series data are scarce. In response to this, the current paper develops a new test for predictability in panels where $N$ is large and $T \geq 2$ can be small or large, or indeed anything in between the two extremes. This consideration represents an advancement when compared to the usual large-$N$ and large-$T$ requirement. The new test is also very general, especially when it comes to the allowable predictors, and it is easy to implement. As an illustration, we consider the Chinese stock market, for which data is only available for 17 years but where the number firms is relatively large, 160.

Department/s

  • Department of Economics

Publishing year

2016

Language

English

Pages

1162-1177

Publication/Series

International Journal of Forecasting

Volume

32

Issue

4

Document type

Journal article

Publisher

Elsevier

Topic

  • Economics and Business

Keywords

  • Panel data
  • Predictive regression
  • Stock return predictability
  • China

Status

Published

ISBN/ISSN/Other

  • ISSN: 1872-8200