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Impact of network investor sentiment and news arrival on jumps

Author

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  • Liu, Wenwen
  • Zhang, Chang
  • Qiao, Gaoxiu
  • Xu, Lei

Abstract

This paper studied the influence of news announcements and network investor sentiment on Chinese stock index and index futures market jumps. A machine learning text analysis algorithm was employed to measure investor forum sentiment. It was found that news arrivals were an important reason for jump occurrences, jumps were significantly associated with network investor sentiment, and while occasionally the news and network investor sentiment resulted in simultaneous market jumps, they appeared to be relatively independent. The network investor sentiment time-lag and asymmetric effects were also tested, from which it was found that network investor sentiment had a significant asymmetric effect on the jumps, but time-lag effects had little influence. News announcements and the top 25% of the extreme network sentiments were found to explain more than 50% of the jumps, with extreme sentiments tending to increase the volatility of the news-related jumps and persistently influencing returns after the news-related jumps.

Suggested Citation

  • Liu, Wenwen & Zhang, Chang & Qiao, Gaoxiu & Xu, Lei, 2022. "Impact of network investor sentiment and news arrival on jumps," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    • Handle: RePEc:eee:ecofin:v:62:y:2022:i:c:s1062940822001218
    DOI: 10.1016/j.najef.2022.101780
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