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Real estate risk measurement and early warning based on PSO-SVM

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Listed:
  • Zhou, Wenwen
  • Chen, Mengyao
  • Yang, Zaoli
  • Song, Xiaobo

Abstract

The measurement and early warning of real estate risk are important to prevent and defuse major financial risks, and they form a basis for high-quality development. This paper assessed the internal and external environments of the real estate market; constructed a real estate risk indicator system from the aspects of market level, real estate enterprises, policy factors and financial institutions; and implemented a PSO-SVM model to measure and warn of real estate risk. Empirical studies were conducted. The results show the following: (1) the synthetic real estate risk index well depicts the cyclical fluctuation of real estate risk in Beijing; (2) the warning model based on the PSO-SVM method exhibits better performance and higher warning accuracy than other models do.

Suggested Citation

  • Zhou, Wenwen & Chen, Mengyao & Yang, Zaoli & Song, Xiaobo, 2021. "Real estate risk measurement and early warning based on PSO-SVM," Socio-Economic Planning Sciences, Elsevier, vol. 77(C).
    • Handle: RePEc:eee:soceps:v:77:y:2021:i:c:s0038012120308387
    DOI: 10.1016/j.seps.2020.101001
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    References listed on IDEAS

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    Cited by:

    1. Shiyu Liu & Ou Liu & Junyang Chen, 2023. "A Review on Business Analytics: Definitions, Techniques, Applications and Challenges," Mathematics, MDPI, vol. 11(4), pages 1-20, February.

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