The complementary role of cross-sectional and time-series information in forecasting stock returns

Qing Zhou, Robert Faff

Research output: Contribution to journalArticleResearchpeer-review

Abstract

While linear time-series models, technical analysis, and momentum models all extract information from past market data, they each interpret data differently. We test the informative role of three representative models and examine the trading performance of a combined forecasting model at the individual stock level. Our results indicate that these models all contain marginal information and complement each other. The combined trading model captures higher upward trending returns and provides the same downward trending returns compared with the buy-and-hold strategy.
LanguageEnglish
Pages113-139
Number of pages27
JournalAustralian Journal of Management
Volume42
Issue number1
DOIs
Publication statusPublished - 2017
Externally publishedYes

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Stock returns
Time series models
Technical analysis
Market data
Momentum

Keywords

  • combination
  • complementarity
  • forecasting
  • out-of-sample
  • stock returns

Cite this

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The complementary role of cross-sectional and time-series information in forecasting stock returns. / Zhou, Qing; Faff, Robert.

In: Australian Journal of Management, Vol. 42, No. 1, 2017, p. 113-139.

Research output: Contribution to journalArticleResearchpeer-review

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