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Measuring Systemic Risk in the Chinese Financial System Based on Asymmetric Exponential Power Distribution

In: Recent Developments in Data Science and Business Analytics

Author

Listed:
  • Helong Li

    (School of Economics and Commerce, South China University of Technology)

  • Tianqi Luo

    (School of Economics and Commerce, South China University of Technology)

  • Liuling Li

    (Institute of Statistics and Econometrics, Economics School, Nankai University)

  • Tiancheng Liu

    (School of Computer, South China University of Technology)

Abstract

We propose an extension of CoVaR approach by employing the Asymmetric Exponential Power Distribution (AEPD) to capture the properties of financial data series such as fat-tailedness and skewness. We prove the new model with AEPD has better goodness-of-fit than traditional model with Gaussian distribution, which means a higher precision. Basing on the Chinese stock market data and the new model, we measure the contribution of 29 financial institutions in bank, security, insurance and other industries.

Suggested Citation

  • Helong Li & Tianqi Luo & Liuling Li & Tiancheng Liu, 2018. "Measuring Systemic Risk in the Chinese Financial System Based on Asymmetric Exponential Power Distribution," Springer Proceedings in Business and Economics, in: Madjid Tavana & Srikanta Patnaik (ed.), Recent Developments in Data Science and Business Analytics, chapter 0, pages 225-232, Springer.
    • Handle: RePEc:spr:prbchp:978-3-319-72745-5_24
    DOI: 10.1007/978-3-319-72745-5_24
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