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Time to delisted status for listed firms in Chinese stock markets: An analysis using a mixture cure model with time-varying covariates

Author

Listed:
  • Qingli Dong
  • Yingwei Peng
  • Peizhi Li

Abstract

Analyzing time to delisted status for listed firms with risk warnings in a stock market is important in risk management of the stock market. This analysis is entangled by the fact that not all listed firms with risk warnings will eventually be delisted, making a standard time-to-event analysis not suitable. The presence of time-varying factors that are related to the listed firms and the macro-economic environment adds another layer of challenge to the analysis. We propose to use a mixture cure model with time-varying covariates to analyze time to delisting in two Chinses stock markets. We identify issues in an existing method and propose a new method to better handle time-varying covariates in the mixture cure model. The model allows an exploration of the association between the probability that a listed firm will never be delisted and time-fixed covariates. The performance of the proposed estimation method is examined using simulation and compared with existing methods. The results of the data analysis reveal a few important time-varying covariates that have significant impacts on the time to delisted status. However, none of the measured time-fixed covariates is found to have a significant impact on the probability of never being delisted.

Suggested Citation

  • Qingli Dong & Yingwei Peng & Peizhi Li, 2022. "Time to delisted status for listed firms in Chinese stock markets: An analysis using a mixture cure model with time-varying covariates," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 73(10), pages 2358-2369, October.
  • Handle: RePEc:taf:tjorxx:v:73:y:2022:i:10:p:2358-2369
    DOI: 10.1080/01605682.2021.1992308
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    Cited by:

    1. Ana López-Cheda & Yingwei Peng & María Amalia Jácome, 2023. "Rejoinder on: Nonparametric estimation in mixture cure models with covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 32(2), pages 513-520, June.

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