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Simulation of Contagion in the Stock Markets Using Cross-Shareholding Networks: A Case from an Emerging Market

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  • Hossein Dastkhan

    (AmirKabir University of Technology (Tehran Polytechnique))

  • Naser Shams Gharneh

    (AmirKabir University of Technology (Tehran Polytechnique))

Abstract

In recent years, simulation of contagion in financial markets is one of the main concerns of the economic and finance researchers and policy makers in order to analyze the effects of different shocks on the contagion. In this paper, we introduce a simulation model to analyze the contagion in financial markets based on the cross-shareholding network of firms. In order to validate the proposed model, we investigate the results of a real dataset from an emerging market. According to different kinds of idiosyncratic and aggregate shocks to the system, we analyze the probability and the extent of contagion. Moreover, to study the effect of market structure, the results of different null models are compared with the real network. The results show that the proposed simulation model and the cross-shareholding network are effectively appropriate in the analysis of contagion and systemic risk in the financial systems. The results of null models indicate that the structural characteristics of the financial networks have significant role in the spread of shocks and financial crisis. The results also reveal that for the networks with homogeneity for degree and weights underestimates the number of infected firms and overestimates the loss percents.

Suggested Citation

  • Hossein Dastkhan & Naser Shams Gharneh, 2019. "Simulation of Contagion in the Stock Markets Using Cross-Shareholding Networks: A Case from an Emerging Market," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1071-1101, March.
    • Handle: RePEc:kap:compec:v:53:y:2019:i:3:d:10.1007_s10614-017-9781-6
    DOI: 10.1007/s10614-017-9781-6
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    3. Cao, Jie & Wen, Fenghua & Stanley, H. Eugene & Wang, Xiong, 2021. "Multilayer financial networks and systemic importance: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 78(C).

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