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Stock return predictability and model instability: Evidence from mainland China and Hong Kong

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  • Hong, Hui
  • Chen, Naiwei
  • O’Brien, Fergal
  • Ryan, James

Abstract

This study examines the predictability of the Shanghai Composite, Shenzhen Composite and the Hang Seng China Enterprise index returns during the period 1993 to 2010, with emphasis on whether considering structural breaks in model parameters improves the stock return predictability.

Suggested Citation

  • Hong, Hui & Chen, Naiwei & O’Brien, Fergal & Ryan, James, 2018. "Stock return predictability and model instability: Evidence from mainland China and Hong Kong," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 132-142.
  • Handle: RePEc:eee:quaeco:v:68:y:2018:i:c:p:132-142
    DOI: 10.1016/j.qref.2017.11.007
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    2. Si, Deng-Kui & Liu, Xi-Hua & Kong, Xianli, 2019. "The comovement and causality between stock market cycle and business cycle in China: Evidence from a wavelet analysis," Economic Modelling, Elsevier, vol. 83(C), pages 17-30.
    3. Yanying Zhang & Yiuman Tse & Gaiyan Zhang, 2022. "Return predictability between industries and the stock market in China," Pacific Economic Review, Wiley Blackwell, vol. 27(2), pages 194-220, May.
    4. Hui Hong & Zhicun Bian & Chien-Chiang Lee, 2021. "COVID-19 and instability of stock market performance: evidence from the U.S," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-18, December.
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    More about this item

    Keywords

    Model instability; structural breaks; return predictability; China; Hong Kong;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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