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Linkages and Spillovers between Internet Finance and Traditional Finance: Evidence from China

Author

Listed:
  • Rongda Chen
  • Huiwen Chen
  • Chenglu Jin
  • Bo Wei
  • Lean Yu

Abstract

Investors, researchers, and policy makers have an urgent need to understand the linkages between internet finance and traditional financial markets. This study collects corresponding daily industrial indices of the banking, security, and insurance industries from the Wind database to depict the traditional financial market in China and uses an online loan comprehensive interest rate index as a proxy for internet finance. The empirical results first show that only internet finance and the banking industry have mutual causality. Then, using conditional value at risk (CoVaR) to measure the degree of spillovers, the risk of internet finance is more likely to spill over to the banking industry, followed by the insurance industry and, lastly, the securities industry. These findings are consistent with the closeness between internet finance and the banking, insurance, and security industries, respectively. The linkage relationships and spillover effect are robust to the method and market index applied.

Suggested Citation

  • Rongda Chen & Huiwen Chen & Chenglu Jin & Bo Wei & Lean Yu, 2020. "Linkages and Spillovers between Internet Finance and Traditional Finance: Evidence from China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(6), pages 1196-1210, May.
    • Handle: RePEc:mes:emfitr:v:56:y:2020:i:6:p:1196-1210
    DOI: 10.1080/1540496X.2019.1658069
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    Citations

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    Cited by:

    1. Chen, Rongda & Wu, Ling & Jin, Chenglu & Wang, Shengnan, 2021. "Unintended investor sentiment on bank financial products: Evidence from China," Emerging Markets Review, Elsevier, vol. 49(C).
    2. Lorraine Muguto & Paul-Francois Muzindutsi, 2022. "A Comparative Analysis of the Nature of Stock Return Volatility in BRICS and G7 Markets," JRFM, MDPI, vol. 15(2), pages 1-27, February.
    3. Zhou, Yang & Xie, Chi & Wang, Gang-Jin & Zhu, You & Uddin, Gazi Salah, 2023. "Analysing and forecasting co-movement between innovative and traditional financial assets based on complex network and machine learning," Research in International Business and Finance, Elsevier, vol. 64(C).
    4. Jin, Chenglu & Lu, Xingyu & Zhang, Yihan, 2022. "Market reaction, COVID-19 pandemic and return distribution," Finance Research Letters, Elsevier, vol. 47(PB).
    5. Zhikai Peng & Jinchuan Ke, 2022. "Spillover Effect of the Interaction between Fintech and the Real Economy Based on Tail Risk Dependent Structure Analysis," Sustainability, MDPI, vol. 14(13), pages 1-22, June.
    6. Chen, Rongda & Wang, Shengnan & Jin, Chenglu & Yu, Jingjing & Zhang, Xinyu & Zhang, Shuonan, 2023. "Comovements between multidimensional investor sentiment and returns on internet financial products," International Review of Financial Analysis, Elsevier, vol. 85(C).
    7. Zheng, Yingfei & Shen, Anran & Li, Ruihai & Yang, Yuhong & Wang, Shengjin & Cheng, Lee-Young, 2023. "Spillover effects between internet financial industry and traditional financial industry: Evidence from the Chinese stock market," Pacific-Basin Finance Journal, Elsevier, vol. 79(C).
    8. Pengpeng Yue & Aslihan Gizem Korkmaz & Zhichao Yin & Haigang Zhou, 2022. "The rise of digital finance: Financial inclusion or debt trap," Papers 2201.09221, arXiv.org.
    9. Yue, Pengpeng & Korkmaz, Aslihan Gizem & Yin, Zhichao & Zhou, Haigang, 2022. "The rise of digital finance: Financial inclusion or debt trap?," Finance Research Letters, Elsevier, vol. 47(PA).
    10. Agata Kliber & Barbara Będowska-Sójka & Aleksandra Rutkowska & Katarzyna Świerczyńska, 2021. "Triggers and Obstacles to the Development of the FinTech Sector in Poland," Risks, MDPI, vol. 9(2), pages 1-27, February.

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