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The impact of guarantee network on the risk of corporate stock price crash: Discussing the moderating effect of internal control quality

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  • Yu, Hongxiang
  • Wang, Ziqi
  • Weng, Yudong
  • Wang, Liying

Abstract

Using data from Chinese listed companies as samples, this paper explores the impact of guarantee networks on the risk of corporate stock price crashes and the moderating effect of internal control quality on this relationship. The empirical analysis yields the following conclusions: guarantee networks can significantly increase the risk of corporate stock price crashes; internal control quality plays a positive moderating role between guarantee networks and the risk of corporate stock price crashes; there is a difference in the impact of guarantee networks on the risk of stock price crashes between state-owned enterprises and non-state-owned enterprises, with a more significant impact on non-state-owned enterprises; and there are differences in the impact of guarantee networks on the risk of stock price crashes among enterprises at different life cycle stages.

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  • Yu, Hongxiang & Wang, Ziqi & Weng, Yudong & Wang, Liying, 2024. "The impact of guarantee network on the risk of corporate stock price crash: Discussing the moderating effect of internal control quality," International Review of Economics & Finance, Elsevier, vol. 96(PC).
  • Handle: RePEc:eee:reveco:v:96:y:2024:i:pc:s1059056024007202
    DOI: 10.1016/j.iref.2024.103728
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    1. Zhang, Xiaoge & Mahadevan, Sankaran, 2021. "Bayesian network modeling of accident investigation reports for aviation safety assessment," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    2. Sun, Xiaojun & Lei, Yalin, 2021. "Research on financial early warning of mining listed companies based on BP neural network model," Resources Policy, Elsevier, vol. 73(C).
    3. Gao, Yang & Li, Yangyang & Wang, Yaojun, 2021. "Risk spillover and network connectedness analysis of China’s green bond and financial markets: Evidence from financial events of 2015–2020," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    4. Yang Li & Yi Pan, 2020. "A Novel Ensemble Deep Learning Model for Stock Prediction Based on Stock Prices and News," Papers 2007.12620, arXiv.org.
    5. Franklin Allen & Xian Gu, 2021. "Shadow banking in China compared to other countries," Manchester School, University of Manchester, vol. 89(5), pages 407-419, September.
    6. Guo, Qingjun & Amin, Shohel & Hao, Qianwen & Haas, Olivier, 2020. "Resilience assessment of safety system at subway construction sites applying analytic network process and extension cloud models," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    7. Hu, Juncheng & Li, Xiaorong & Duncan, Keith & Xu, Jia, 2020. "Corporate relationship spending and stock price crash risk: Evidence from China's anti-corruption campaign," Journal of Banking & Finance, Elsevier, vol. 113(C).
    8. Reboredo, Juan C. & Ugolini, Andrea & Aiube, Fernando Antonio Lucena, 2020. "Network connectedness of green bonds and asset classes," Energy Economics, Elsevier, vol. 86(C).
    9. Helder Sebastião & Pedro Godinho, 2021. "Forecasting and trading cryptocurrencies with machine learning under changing market conditions," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-30, December.
    10. Gunther Capelle-Blancard & Adrien Desroziers, 2020. "The stock market is not the economy? Insights from the Covid-19 crisis," Post-Print hal-03252106, HAL.
    11. Cem Cakmakli & Selva Demiralp & Sebnem Kalemli-Ozcan & Sevcan Yesiltas & Muhammed A. Yildirim, 2020. "COVID-19 and Emerging Markets: An Epidemiological Model with International Production Networks and Capital Flows," IMF Working Papers 2020/133, International Monetary Fund.
    12. Lai, Yujie & Hu, Yibo, 2021. "A study of systemic risk of global stock markets under COVID-19 based on complex financial networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    13. Sajid, Zaman, 2021. "A dynamic risk assessment model to assess the impact of the coronavirus (COVID-19) on the sustainability of the biomass supply chain: A case study of a U.S. biofuel industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    14. Briola, Antonio & Vidal-Tomás, David & Wang, Yuanrong & Aste, Tomaso, 2023. "Anatomy of a Stablecoin’s failure: The Terra-Luna case," Finance Research Letters, Elsevier, vol. 51(C).
    15. Ben Hambly & Renyuan Xu & Huining Yang, 2021. "Recent Advances in Reinforcement Learning in Finance," Papers 2112.04553, arXiv.org, revised Feb 2023.
    16. Ben Hambly & Renyuan Xu & Huining Yang, 2023. "Recent advances in reinforcement learning in finance," Mathematical Finance, Wiley Blackwell, vol. 33(3), pages 437-503, July.
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    2. Jiang, Tao & Fan, Jiabiao, 2025. "How does the policy of additional deduction for research and development expenses affect credit risk pricing capability in enterprises?," Finance Research Letters, Elsevier, vol. 77(C).

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