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Quantitative evaluation of consecutive resilience cycles in stock market performance: A systems-oriented approach

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  • Tang, Junqing
  • Heinimann, Hans
  • Khoja, Layla

Abstract

Financial markets can be seen as complex systems that are constantly evolving and sensitive to external disturbance, such as financial risks and economic instabilities. Analysis of resilient market performance, therefore, becomes useful for investors. From a systems perspective, this paper proposes a novel function-based resilience metric that considers the effect of two fault-tolerance thresholds: the Robustness Range (RR) and the Elasticity Threshold (ET). We examined the consecutive resilience cycles and their dynamics in the performance of three stock markets, NASDAQ, SSE, and NYSE. The proposed metric was also compared with three well-documented resilience models. The results showed that this new metric could satisfactorily quantify the time-varying resilience cycles in the multi-cycle volatile performance of stock markets while also being more feasible in comparative analysis. Furthermore, analysis of dynamics revealed that those consecutive resilience cycles in market performance were distributed non-linearly, following a power-law distribution in the upper tail. Finally, sensitivity tests demonstrated the large-value resilience cycles were relatively sensitive to changes in RR. In practice, RR could indicate investors’ psychological capability to withstand downturns. It supports the observation that perception on the market’s resilient responses may vary among investors. This study provides a new tool and valuable insights for researchers, practitioners, and investors when evaluating market performance.

Suggested Citation

  • Tang, Junqing & Heinimann, Hans & Khoja, Layla, 2019. "Quantitative evaluation of consecutive resilience cycles in stock market performance: A systems-oriented approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 532(C).
    • Handle: RePEc:eee:phsmap:v:532:y:2019:i:c:s0378437119310350
    DOI: 10.1016/j.physa.2019.121794
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    Cited by:

    1. Tang, Junqing & Xu, Lei & Luo, Chunling & Ng, Tsan Sheng Adam, 2021. "Multi-disruption resilience assessment of rail transit systems with optimized commuter flows," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    2. Jie Huang & Zimin Sun & Minzhe Du, 2022. "Differences and Drivers of Urban Resilience in Eight Major Urban Agglomerations: Evidence from China," Land, MDPI, vol. 11(9), pages 1-18, September.

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