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Stock market interdependence between China and the world: A multi-factor R-squared approach

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  • He, Hongbo
  • Chen, Shou
  • Yao, Shujie
  • Ou, Jinghua

Abstract

Using the daily return indexes of 39 industries obtained from DataStream database during 3 January 2000–31 May 2011 of the world stock markets and the multi-factor R-squared approach, we derive a normalized index to analyze the impact of China’s financial liberalization on its stock market interdependence with the world. It is found that China’s financial market reforms after its WTO accession have significantly enhanced market interdependence.

Suggested Citation

  • He, Hongbo & Chen, Shou & Yao, Shujie & Ou, Jinghua, 2015. "Stock market interdependence between China and the world: A multi-factor R-squared approach," Finance Research Letters, Elsevier, vol. 13(C), pages 125-129.
    • Handle: RePEc:eee:finlet:v:13:y:2015:i:c:p:125-129
    DOI: 10.1016/j.frl.2015.02.005
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    References listed on IDEAS

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    8. He, Hongbo & Chen, Shou & Yao, Shujie & Ou, Jinghua, 2014. "Financial liberalisation and international market interdependence: Evidence from China’s stock market in the post-WTO accession period," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 434-444.
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    Cited by:

    1. Saiful Izzuan Hussain & Steven Li, 2018. "The dynamic dependence between stock markets in the greater China economic area: a study based on extreme values and copulas," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 32(2), pages 207-233, May.
    2. Yarovaya, Larisa & Brzeszczyński, Janusz & Lau, Chi Keung Marco, 2016. "Volatility spillovers across stock index futures in Asian markets: Evidence from range volatility estimators," Finance Research Letters, Elsevier, vol. 17(C), pages 158-166.
    3. Liu, Jing & Ma, Feng & Zhang, Yaojie, 2019. "Forecasting the Chinese stock volatility across global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 466-477.
    4. Liew, Venus Khim-Sen & Puah, Chin-Hong, 2020. "Chinese stock market sectoral indices performance in the time of novel coronavirus pandemic," MPRA Paper 100414, University Library of Munich, Germany, revised 28 Apr 2020.
    5. Hussain, Saiful Izzuan & Li, Steven, 2018. "The dependence structure between Chinese and other major stock markets using extreme values and copulas," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 421-437.
    6. Yao, Shujie & He, Hongbo & Chen, Shou & Ou, Jinghua, 2018. "Financial liberalization and cross-border market integration: Evidence from China's stock market," International Review of Economics & Finance, Elsevier, vol. 58(C), pages 220-245.
    7. Ashfaq, Saleha & Tang, Yong & Maqbool, Rashid, 2020. "Dynamics of spillover network among oil and leading Asian oil trading countries’ stock markets," Energy, Elsevier, vol. 207(C).
    8. Meng, Xiangcai & Huang, Chia-Hsing, 2019. "The time-frequency co-movement of Asian effective exchange rates: A wavelet approach with daily data," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 131-148.
    9. Duc Hong Vo, 2021. "Portfolio Optimization and Diversification in China: Policy Implications for Vietnam and Other Emerging Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 57(1), pages 223-238, January.
    10. You, Kefei & Raju Chinthalapati, V.L. & Mishra, Tapas & Patra, Ramakanta, 2024. "International trade network and stock market connectedness: Evidence from eleven major economies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).
    11. Lu, Jingen & Chen, Xiaohong & Liu, Xiaoxing, 2018. "Stock market information flow: Explanations from market status and information-related behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 837-848.
    12. Changqing, Luo & Chi, Xie & Cong, Yu & Yan, Xu, 2015. "Measuring financial market risk contagion using dynamic MRS-Copula models: The case of Chinese and other international stock markets," Economic Modelling, Elsevier, vol. 51(C), pages 657-671.
    13. Xiaomeng Ma & Dong Zou & Chuanchao Huang & Shuliang Lv, 2020. "China’s growing influence and risk in Asia–Pacific stock markets: evidence from spillover effects and market integration," Risk Management, Palgrave Macmillan, vol. 22(4), pages 338-361, December.
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    15. Vo, Xuan Vinh & Ellis, Craig, 2018. "International financial integration: Stock return linkages and volatility transmission between Vietnam and advanced countries," Emerging Markets Review, Elsevier, vol. 36(C), pages 19-27.

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    More about this item

    Keywords

    Market interdependence; Principal component analysis; Multi-factor R-squared;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • F36 - International Economics - - International Finance - - - Financial Aspects of Economic Integration
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation

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