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

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  • Junqing Tang
  • Hans R. Heinimann

Abstract

Financial markets can be seen as complex systems that are constantly evolving and sensitive to external disturbance, such as systemic 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 two stock markets, NASDAQ and SSE. 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 behavior 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 insight for researchers, practitioners, and investors when evaluating market performance.

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  • Junqing Tang & Hans R. Heinimann, 2019. "Quantitative evaluation of consecutive resilience cycles in stock market performance: A systems-oriented approach," Papers 1903.03201, arXiv.org.
    • Handle: RePEc:arx:papers:1903.03201
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    References listed on IDEAS

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    2. 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).

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