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A new perspective on financial anomalies in emerging markets : the case of China

Author

Listed:
  • Zhichao Zhang

    (EM - EMLyon Business School)

  • Wai Sun
  • Hua Wang

Abstract

Financial anomalies in emerging markets can be caused by very different reasons than that in mature markets. In a Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, we examine financial anomalies in emerging markets from a new perspective, which focuses on heavy political interventions. In the context of China, we show that political consideration of the government can be a critical force that drives the monthly anomaly in the stock market. The Chinese case indicates that usual explanations for the monthly anomaly or the January effect may become invalid in an environment where political intervention is a dominant force in the stock market. Typical of a policy-driven market that prevails in emerging economies, indicate no evidence for the January effect in China, neither its mirror version, the Chinese New Year effect. Rather, returns abnormality is found to occur in March when China is in the political high season. This March effect is likely a result of political manoeuvre by the government to make the appearance of a stable and thriving stock market, which serves the political purpose of preventing social resentment in a politically sensitive time. This shows political window dressing can be an important cause of financial anomalies, which has been largely neglected in the literature.

Suggested Citation

  • Zhichao Zhang & Wai Sun & Hua Wang, 2008. "A new perspective on financial anomalies in emerging markets : the case of China," Post-Print hal-02313413, HAL.
  • Handle: RePEc:hal:journl:hal-02313413
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    Cited by:

    1. Saša Popović & Andrija Đurović, 2014. "Intraweek and intraday trade anomalies: evidence from FOREX market," Applied Economics, Taylor & Francis Journals, vol. 46(32), pages 3968-3979, November.
    2. Yuan, Tian & Gupta, Rakesh, 2014. "Chinese Lunar New Year effect in Asian stock markets, 1999–2012," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(4), pages 529-537.
    3. Rima Turk Ariss & Rasoul Rezvanian & Seyed M. Mehdian, 2012. "WTO membership, ownership deregulation, and market efficiency: evidence from China," Applied Financial Economics, Taylor & Francis Journals, vol. 22(3), pages 177-195, February.
    4. Ali Akyol, 2011. "Stock returns around nontrading periods: evidence from an emerging market," Applied Financial Economics, Taylor & Francis Journals, vol. 21(20), pages 1549-1560.
    5. Paul McGuinness & Richard Harris, 2011. "Comparison of the 'turn-of-the-month' and lunar new year return effects in three Chinese markets: Hong Kong, Shanghai and Shenzhen," Applied Financial Economics, Taylor & Francis Journals, vol. 21(13), pages 917-929.
    6. Gabe J. de Bondt & Tuomas A. Peltonen & Daniel Santabárbara, 2010. "Booms and busts in China's stock market: Estimates based on fundamentals," Working Papers 1032, Banco de España.
    7. Shuang Feng & Jon T. Stewart, 2015. "A Review of Market Segmentation and Inefficiencies of the Chinese Stock Market," International Journal of Finance & Banking Studies, Center for the Strategic Studies in Business and Finance, vol. 4(4), pages 18-28, October.
    8. Gao, Yang & Li, Yangyang & Wang, Yaojun, 2021. "Risk spillover and network connectedness analysis of China’s green bond and financial markets: Evidence from financial events of 2015–2020," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).

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