Cross-Sectional Stock Return Predictability in China

42 Pages Posted: 11 Apr 2012

See all articles by Nusret Cakici

Nusret Cakici

Fordham university

Kalok Chan

CUHK Business School

Kudret Topyan

Manhattan College - Department of Economics and Finance

Date Written: November 10, 2011

Abstract

Cross-sectional stock return predictability has always been an intriguing issue for the researchers as it relates to a number of resilient puzzles in finance. This paper provides a comprehensive analysis on the stock return predictability in China form January 1994 to March 2011 by employing both portfolio method and cross-sectional regressions. We find strong predictive power of size, price, book-to-market ratio, cash-flow-to-price ratio, and earnings-to-price ratio. The total as well as idiosyncratic volatility are also consistent stock return predictors in China. The results exist for stocks listed in Shanghai Stock Exchange as well as Shenzhen Stock Exchange. Unlike evidence for the other markets (e.g. U.S), the momentum fails to qualify as a useful predictor in the portfolio method. It is only when used with other predictors that it exhibits predictive power for the Chinese stocks. Overall, the variables related to cheapness of stocks such as book-to-market ratio and cash-flow-to-price ratio demonstrate reliable forecast power, but earnings-to-price ratio is less reliable.

Keywords: Chinese stock returns, Stock return predictors, Momentum, Stock Cheapness

JEL Classification: G10, G11,G12

Suggested Citation

Cakici, Nusret and Chan, Kalok and Topyan, Kudret, Cross-Sectional Stock Return Predictability in China (November 10, 2011). Available at SSRN: https://ssrn.com/abstract=2038497 or http://dx.doi.org/10.2139/ssrn.2038497

Nusret Cakici

Fordham university ( email )

113 West 60th Street
New York, NY 10023
United States
2017473227 (Phone)
07446 (Fax)

Kalok Chan

CUHK Business School ( email )

Hong Kong
852 3943 9988 (Phone)

Kudret Topyan (Contact Author)

Manhattan College - Department of Economics and Finance ( email )

Riverdale, NY 10471
United States

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
926
Abstract Views
4,045
Rank
46,805
PlumX Metrics