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

Zhou, Qing and Faff, Robert (2015) The complementary role of cross-sectional and time-series information in forecasting stock returns. Australian Journal of Management, . doi:10.1177/0312896215575888


Author Zhou, Qing
Faff, Robert
Title The complementary role of cross-sectional and time-series information in forecasting stock returns
Journal name Australian Journal of Management   Check publisher's open access policy
ISSN 1327-2020
0312-8962
Publication date 2015
Sub-type Article (original research)
DOI 10.1177/0312896215575888
Open Access Status Not yet assessed
Total pages 27
Place of publication London, United Kingdom
Publisher Sage Publications
Collection year 2016
Language eng
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.
Keyword Combination
Complementarity
Forecasting
Out-of-sample
Stock returns
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
UQ Business School Publications
 
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Created: Mon, 10 Aug 2015, 10:53:35 EST by Karen Morgan on behalf of UQ Business School