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Research on external financial risk measurement of China real estate

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  • Yuexiang Jiang
  • Luyuan Zheng
  • Jiazhen Wang

Abstract

This study applies the method proposed by Diebold and Yilmaz to construct a spillover effect index with which we compare the bilateral information spillover effect and time‐varying characteristics of China's real estate markets to those of representative international financial markets from July 2005 to March 2018 to measure the financial risks in China's real estate markets. The empirical results show the following. (a) There is a significant information spillover effect between China's real estate markets and related stock markets, and China's real estate is in a net information receiving position. (b) After 2016, China's real estate financial risks entered a downward adjustment cycle, and financial risks have gradually declined. These results suggest that Chinese real estate markets' “de‐inventory” has achieved remarkable results and that real estate financial risks have been significantly reduced. However, due to China's limited real estate financial investment channels, the nation's real estate markets should still be cautiously controlled and regulated to respond to potential real estate financial risk.

Suggested Citation

  • Yuexiang Jiang & Luyuan Zheng & Jiazhen Wang, 2021. "Research on external financial risk measurement of China real estate," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5472-5484, October.
    • Handle: RePEc:wly:ijfiec:v:26:y:2021:i:4:p:5472-5484
    DOI: 10.1002/ijfe.2075
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    References listed on IDEAS

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    1. Ing-Haw Cheng & Wei Xiong, 2014. "Financialization of Commodity Markets," Annual Review of Financial Economics, Annual Reviews, vol. 6(1), pages 419-441, December.
    2. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    3. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    4. Lin, Wen-Yuan & Tsai, I-Chun, 2019. "Trader differences in Shanghai’s A-share and B-share markets: Effects on interaction with the Shanghai housing market," Journal of Asian Economics, Elsevier, vol. 64(C), pages 1-1.
    5. Nafeesa Yunus, 2012. "Modeling Relationships among Securitized Property Markets, Stock Markets and Macroeconomic Variables," Journal of Real Estate Research, American Real Estate Society, vol. 34(2), pages 127-156.
    6. Hui, Eddie C.M. & Chen, Jia, 2012. "Investigating the change of causality in emerging property markets during the financial tsunami," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(15), pages 3951-3962.
    7. Chan, Kam Fong & Treepongkaruna, Sirimon & Brooks, Robert & Gray, Stephen, 2011. "Asset market linkages: Evidence from financial, commodity and real estate assets," Journal of Banking & Finance, Elsevier, vol. 35(6), pages 1415-1426, June.
    8. Hui, Eddie Chi-man & Chan, Ka Kwan Kevin, 2014. "The global financial crisis: Is there any contagion between real estate and equity markets?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 216-225.
    9. Silvennoinen, Annastiina & Thorp, Susan, 2013. "Financialization, crisis and commodity correlation dynamics," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 42-65.
    10. Greenwood-Nimmo, Matthew & Nguyen, Viet Hoang & Rafferty, Barry, 2016. "Risk and return spillovers among the G10 currencies," Journal of Financial Markets, Elsevier, vol. 31(C), pages 43-62.
    11. Edward Glaeser & Wei Huang & Yueran Ma & Andrei Shleifer, 2017. "A Real Estate Boom with Chinese Characteristics," Journal of Economic Perspectives, American Economic Association, vol. 31(1), pages 93-116, Winter.
    12. Fengyun Liu & Deqiang Liu & Reza Malekian & Zhixiong Li & Deqing Wang, 2017. "A measurement model for real estate bubble size based on the panel data analysis: An empirical case study," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-26, March.
    13. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    14. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    15. repec:iae:iaewps:wp2016n4 is not listed on IDEAS
    16. Xiaojing Zhang & Tao Sun, 2006. "China's Current Real Estate Cycle and Potential Financial Risks," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 14(4), pages 57-74, August.
    17. Eddie C.M. Hui & Ka Kwan Kevin Chan, 2013. "The European sovereign debt crisis: contagion across European real estate markets," Journal of Property Research, Taylor & Francis Journals, vol. 30(2), pages 87-102, June.
    18. Chi-Wei Su & Xiao-Cui Yin & Hsu-Ling Chang & Hai-Gang Zhou, 2019. "Are the stock and real estate markets integrated in China?," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(4), pages 741-760, December.
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