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Arbitrage risk and the cross-section of stock returns: Evidence from China

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  • Lin, Yu En
  • Chu, Chien Chi
  • Omura, Akihiro
  • Li, Bin
  • Roca, Eduardo

Abstract

We demonstrate that arbitrage risk, constructed using three measures — noise trader risk, trading cost and information uncertainty — can predict the return of stocks cross-sectionally in China. The findings are broadly consistent even when out-of-sample tests are conducted using the Fama-MacBeth cross-sectional regression approach. We also construct hypothetical portfolios using the information arising from arbitrage risk and find the existence of abnormal returns which is robust to the use of various portfolios constructed by re-sampling the observations through multiple approaches (e.g., by market capitalization and by book-to-market ratio). Lastly, we reconstruct our portfolios by considering the unique nature of the Chinese stock market (e.g., the dominance of individual investors). Our trading strategies again successfully obtain abnormal returns, suggesting that arbitrage risk can be useful to construct effective investment portfolios in China.

Suggested Citation

  • Lin, Yu En & Chu, Chien Chi & Omura, Akihiro & Li, Bin & Roca, Eduardo, 2020. "Arbitrage risk and the cross-section of stock returns: Evidence from China," Emerging Markets Review, Elsevier, vol. 43(C).
    • Handle: RePEc:eee:ememar:v:43:y:2020:i:c:s1566014118303327
    DOI: 10.1016/j.ememar.2019.03.007
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    2. An-Pin Wei & Chi-Lu Peng & Hao-Chen Huang & Shang-Pao Yeh, 2020. "Effects of Corporate Social Responsibility on Firm Performance: Does Customer Satisfaction Matter?," Sustainability, MDPI, vol. 12(18), pages 1-18, September.
    3. Danyan Wen & Mengxi He & Yaojie Zhang & Yudong Wang, 2022. "Forecasting realized volatility of Chinese stock market: A simple but efficient truncated approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 230-251, March.

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