The complementary role of cross-sectional and time-series information in forecasting stock returns-Reference-Cited by-同舟云学术

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

Published:2016-07-09 Issue:1 Volume:42 Page:113-139
ISSN:0312-8962
Container-title:Australian Journal of Management
language:en
Short-container-title:Australian Journal of Management

Author:

Zhou Qing¹,Faff Robert²

Affiliation:

1. UQ Business School, The University of Queensland, Australia; School of Management, Xi’an Jiaotong University, China

2. UQ Business School, The University of Queensland, Australia; Department of Accounting and Finance, University of Strathclyde, UK

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.

Publisher

SAGE Publications

Subject

General Business, Management and Accounting

Link

http://journals.sagepub.com/doi/pdf/10.1177/0312896215575888

Reference63 articles.

1. Using genetic algorithms to find technical trading rules1Helpful comments were made by Adam Dunsby, Lawrence Fisher, Steven Kimbrough, Paul Kleindorfer, Michele Kreisler, James Laing, Josef Lakonishok, George Mailath, and seminar participants at Institutional Investor, J.P. Morgan, the NBER Asset Pricing Program, Ohio State University, Purdue University, the Santa Fe Institute, Rutgers University, Stanford University, University of California, Berkeley, University of Michigan, University of Pennsylvania, University of Utah, Washington University (St. Louis), and the 1995 AFA Meetings in Washington, D.C. We are particularly grateful to Kenneth R. French (the referee), and G. William Schwert (the editor) for their suggestions. Financial support from the National Science Foundation is gratefully acknowledged by the first author and from the Academy of Finland by the second and from the Geewax-Terker Program in Financial Instruments by both. Correspondence should be addressed to Franklin Allen, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104-6367.1

2. The Combination of Forecasts

3. Fundamental and technical analysis: substitutes or complements?

4. Market Statistics and Technical Analysis: The Role of Volume

5. Simple Technical Trading Rules and the Stochastic Properties of Stock Returns

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