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Testing for expected return and market price of risk in Chinese A and B share markets: A geometric Brownian motion and multivariate GARCH model approach

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  • Zhu, Jie

Abstract

There exist dual listed stocks which are issued by the same company in some stock markets. Although these stocks bare the same firm-specific risks and enjoy identical dividends and voting policies, they are priced differently. Some previous studies show this seeming deviation from the law of one price can be solved by allowing different expected returns and market prices of risk for investors holding heterogeneous beliefs. This paper provides empirical evidence for that argument by testing the expected return and market price of risk between Chinese A and B shares listed in Shanghai and Shenzhen stock markets. Models with dynamic of Geometric Brownian Motion are adopted. Multivariate GARCH models are also introduced to capture the feature of time-varying volatility in stock returns. The results suggest that the different pricing can be explained by the difference in expected returns between A and B shares. However, the difference between market price of risk is insignificant for both markets if GARCH models are adopted.

Suggested Citation

  • Zhu, Jie, 2009. "Testing for expected return and market price of risk in Chinese A and B share markets: A geometric Brownian motion and multivariate GARCH model approach," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2633-2653.
    • Handle: RePEc:eee:matcom:v:79:y:2009:i:8:p:2633-2653
    DOI: 10.1016/j.matcom.2008.12.005
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    References listed on IDEAS

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    Cited by:

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    2. Lin, Saiyan & Chen, Rongda & Lv, Zhihong & Zhou, Tianqing & Jin, Chenglu, 2019. "Integrated measurement of liquidity risk and market risk of company bonds based on the optimal Copula model," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    3. Li, Johnny Siu-Hang & Ng, Andrew C.Y. & Chan, Wai-Sum, 2015. "Managing financial risk in Chinese stock markets: Option pricing and modeling under a multivariate threshold autoregression," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 217-230.
    4. John Francis T. Diaz, 2018. "Volatility Dynamics in the ASEAN– China Free Trade Agreement," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(3), pages 287-306, December.
    5. Allen, David E. & Gao, Jiti & McAleer, Michael, 2009. "Modelling and managing financial risk: An overview," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2521-2524.

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    More about this item

    Keywords

    China stock market; Market segmentation; Expected return; Market price of risk; Multivariate GARCH;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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