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Hybrid investment motivations lead to heavy tails in M&A dynamics: Empirical evidence from China’s stock market

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  • Hou, Rui
  • Luo, Zhi
  • Cheng, Mingbao
  • Zhu, Yu-xiao
  • Wu, Jia-wen

Abstract

The time interval distribution law of mergers and acquisitions (M&As) is a key breakthrough in understanding the M&As dynamics in financial markets. Using the stock composite index (SCI) data of the Shanghai Stock Exchange (SSE) and the merger and acquisition (M&A) activities data in China’s stock market (1996–2014) as samples, we analyze the heavy-tailed distribution characteristics of the M&As time intervals and test the positive correlation between the SCI volatility and M&A activity fluctuations. We then establish an M&A dynamics model based on mixed investment motives and verify the correctness of the model through simulations. The result shows that the different volatility signals of SCI will trigger different investment motivations on short-term speculative and long-term value M&A, which are the direct reason for the heavy-tailed distribution phenomenon of M&A time intervals in financial markets.

Suggested Citation

  • Hou, Rui & Luo, Zhi & Cheng, Mingbao & Zhu, Yu-xiao & Wu, Jia-wen, 2019. "Hybrid investment motivations lead to heavy tails in M&A dynamics: Empirical evidence from China’s stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 528(C).
    • Handle: RePEc:eee:phsmap:v:528:y:2019:i:c:s0378437119308192
    DOI: 10.1016/j.physa.2019.121399
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