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A Time Series Analysis of the Shanghai and New York Stock Price Indices

Author

Listed:
  • Gregory C. Chow

    (Department of Economics, Princeton University)

  • Caroline C. Lawler

    (Department of Economics, Princeton University)

Abstract

A time series analysis of the Shanghai and New York Stock Exchange composite price indices is provided to compare the weekly rates of return and volatilities of these two markets and to study their co-movement in 1992-2002. The rate of return and volatility of the Shanghai market were higher. The rates of returns in the two markets were approximately serially uncorrelated and mutually uncorrelated. Volatility, as measured by the absolute change in the rate of return, has positive serially correlations in both markets as expected, but the autoregressions are temporarily unstable. Surprisingly the volatility measures of the two markets are significantly negatively correlated. Volatility in each market was found to Granger cause volatility in the other market negatively. This spurious correlation is explained by the negative correlations of macroeconomic fundamentals in the United States and China as indicated by a negative correlation between the rates of change in their GDP while their capital markets are not integrated. The analysis has implications for the use of autoregressions and Granger causality tests, and the interpretation of spurious correlation.

Suggested Citation

  • Gregory C. Chow & Caroline C. Lawler, 2003. "A Time Series Analysis of the Shanghai and New York Stock Price Indices," Annals of Economics and Finance, Society for AEF, vol. 4(1), pages 17-35, May.
    • Handle: RePEc:cuf:journl:y:2003:v:4:i:1:p:17-35
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    References listed on IDEAS

    as
    1. Chow, Gregory C. & Fan, Zhao-zhi & Hu, Jin-yan, 1999. "Shanghai Stock Prices as Determined by the Present-Value Model," Journal of Comparative Economics, Elsevier, vol. 27(3), pages 553-561, September.
    2. Yao, Chengxi, 1998. "Stock Market and Futures Market in the People's Republic of China," OUP Catalogue, Oxford University Press, number 9780195907254, Decembrie.
    3. Bekaert, Geert & Harvey, Campbell R., 1997. "Emerging equity market volatility," Journal of Financial Economics, Elsevier, vol. 43(1), pages 29-77, January.
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    Cited by:

    1. Jan F. Kiviet & Zhenxi Chen, 2018. "A Critical Appraisal of Studies Analyzing Co-movement of International Stock Markets," Annals of Economics and Finance, Society for AEF, vol. 19(1), pages 151-196, May.
    2. Haakon Kavli & Kevin Kotzé, 2014. "Spillovers in Exchange Rates and the Effects of Global Shocks on Emerging Market Currencies," South African Journal of Economics, Economic Society of South Africa, vol. 82(2), pages 209-238, June.
    3. Frank J. Fabozzi & Radu Tunaru & Tony Wu, 2004. "Modeling Volatility for the Chinese Equity Markets," Annals of Economics and Finance, Society for AEF, vol. 5(1), pages 79-92, May.
    4. Chow, Gregory C. & Liu, Changjiang & Niu, Linlin, 2011. "Co-movements of Shanghai and New York stock prices by time-varying regressions," Journal of Comparative Economics, Elsevier, vol. 39(4), pages 577-583.
    5. David G. McMillan & Isabel Ruiz, 2009. "Volatility dynamics in three euro exchange rates: correlations, spillovers and commonality," International Journal of Financial Markets and Derivatives, Inderscience Enterprises Ltd, vol. 1(1), pages 64-74.
    6. Zhou, Xinmiao & Qian, Huanhuan & Pérez-Rodríguez, Jorge. V. & González López-Valcárcel, Beatriz, 2020. "Risk dependence and cointegration between pharmaceutical stock markets: The case of China and the USA," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    7. David McMillan & Isabel Ruiz & Alan Speight, 2010. "Correlations and spillovers among three euro rates: evidence using realised variance," The European Journal of Finance, Taylor & Francis Journals, vol. 16(8), pages 753-767.
    8. McMillan, David G. & Speight, Alan E.H., 2010. "Return and volatility spillovers in three euro exchange rates," Journal of Economics and Business, Elsevier, vol. 62(2), pages 79-93, March.
    9. repec:zbw:bofitp:2011_016 is not listed on IDEAS
    10. Kiviet Jan F., 2017. "Discriminating between (in)valid External Instruments and (in)valid Exclusion Restrictions," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-9, January.
    11. Chow, Gregory C. & Liu, Changjiang & Niu, Linlin, 2011. "Co-movements of Shanghai and New York stock prices by time-varying regressions," Journal of Comparative Economics, Elsevier, vol. 39(4), pages 577-583.
    12. repec:wyi:journl:002146 is not listed on IDEAS
    13. Thomas C. Chiang & Lanjun Lao & Qingfeng Xue, 2016. "Comovements between Chinese and global stock markets: evidence from aggregate and sectoral data," Review of Quantitative Finance and Accounting, Springer, vol. 47(4), pages 1003-1042, November.
    14. Luke Lin & Wen-Yuan Lin, 2018. "Does the major market influence transfer? Alternative effect on Asian stock markets," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 1169-1200, May.
    15. Chen, Xiaoyu & Chiang, Thomas C., 2016. "Stock returns and economic forces—An empirical investigation of Chinese markets," Global Finance Journal, Elsevier, vol. 30(C), pages 45-65.
    16. Chen, Jian & Jiang, Fuwei & Li, Hongyi & Xu, Weidong, 2016. "Chinese stock market volatility and the role of U.S. economic variables," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 70-83.
    17. Ming Lin & Changjiang Liu & Linlin Niu, 2013. "Bayesian Estimation of Wishart Autoregressive Stochastic Volatility Model," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    18. Jan F. Kiviet & Zhenxi Chen, 2016. "A critical appraisal of studies analyzing co-movement of international stock markets with a focus on East-Asian indices," Economic Growth Centre Working Paper Series 1606, Nanyang Technological University, School of Social Sciences, Economic Growth Centre.

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    More about this item

    Keywords

    Time series analysis; Rate of return; Volatility; Autoregressions; Granger causality; Spurious correlation; Shanghai stock price; New York stock price;
    All these keywords.

    JEL classification:

    • 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
    • G1 - Financial Economics - - General Financial Markets

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