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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. Bekaert, Geert & Harvey, Campbell R., 1997. "Emerging equity market volatility," Journal of Financial Economics, Elsevier, vol. 43(1), pages 29-77, January.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. 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.
    2. 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.
    3. repec:cuf:journl:y:2018:v:19:i:1:kiviet:chen is not listed on IDEAS
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.

    More about this item

    Keywords

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

    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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