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Testing for Expected Return and Market Price of Risk in Chinese A-B Share Market: A Geometric Brownian Motion and Multivariate GARCH Model Approach

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  • Jie Zhu

    (School of Economics and Management, University of Aarhus, Denmark and CREATES)

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 risk 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 due to different expected return and market price 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 in Chinese stock markets. However, the difference between market prices of risk is insignificant for both markets if GARCH models are adopted.

Suggested Citation

  • Jie Zhu, 2008. "Testing for Expected Return and Market Price of Risk in Chinese A-B Share Market: A Geometric Brownian Motion and Multivariate GARCH Model Approach," CREATES Research Papers 2008-15, Department of Economics and Business Economics, Aarhus University.
    • Handle: RePEc:aah:create:2008-15
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    2. Enrico Geretto & Rubens Pauluzzo, 2012. "Stock Exchange Markets in China: Structure and Main Problems," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 19(1), pages 89-106, September.

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    More about this item

    Keywords

    China stock market; market segmentation; expected return; market price of risk; GBM; 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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