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A model for the evaluation of systemic risk in stock markets

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  • Caetano, Marco Antonio Leonel
  • Yoneyama, Takashi

Abstract

Systemic risk refers to the possibility of a collapse of an entire financial system or market, differing from the risk associated with any particular individual or a group pertaining to the system, which may include banks, government, brokers, and creditors. After the 2008 financial crisis, a significant amount of effort has been directed to the study of systemic risk and its consequences around the world. Although it is very difficult to predict when people begin to lose confidence in a financial system, it is possible to model the relationships among the stock markets of different countries and perform a Monte Carlo-type analysis to study the contagion effect. Because some larger and stronger markets influence smaller ones, a model inspired by a catalytic chemical model is proposed. In chemical reactions, reagents with higher concentrations tend to favor their conversion to products. In order to modulate the conversion process, catalyzers may be used. In this work, a mathematical modeling is proposed with bases on the catalytic chemical reaction model. More specifically, the Hang Seng and Dow Jones indices are assumed to dominate Ibovespa (the Brazilian Stock Market index), such that the indices of strong markets are taken as being analogous to the concentrations of the reagents and the indices of smaller markets as concentrations of products. The role of the catalyst is to model the degree of influence of one index on another. The actual data used to fit the model parameter consisted of the Hang Seng index, Dow Jones index, and Ibovespa, since 1993. “What if” analyses were carried out considering some intervention policies.

Suggested Citation

  • Caetano, Marco Antonio Leonel & Yoneyama, Takashi, 2011. "A model for the evaluation of systemic risk in stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(12), pages 2368-2374.
    • Handle: RePEc:eee:phsmap:v:390:y:2011:i:12:p:2368-2374
    DOI: 10.1016/j.physa.2011.02.034
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    References listed on IDEAS

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    Cited by:

    1. Wu, Tao & Gao, Xiangyun & An, Sufang & Liu, Siyao, 2021. "Time-varying pattern causality inference in global stock markets," International Review of Financial Analysis, Elsevier, vol. 77(C).
    2. Chen, Lin & Han, Qian & Qiao, Zhilin & Stanley, H. Eugene, 2020. "Correlation analysis and systemic risk measurement of regional, financial and global stock indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    3. Silva, Walmir & Kimura, Herbert & Sobreiro, Vinicius Amorim, 2017. "An analysis of the literature on systemic financial risk: A survey," Journal of Financial Stability, Elsevier, vol. 28(C), pages 91-114.

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