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Trading and non-trading period Internet information flow and intraday return volatility

Author

Listed:
  • Shen, Dehua
  • Zhang, Wei
  • Xiong, Xiong
  • Li, Xiao
  • Zhang, Yongjie

Abstract

This paper employs the news appeared in Baidu News as the proxy for Internet information flow, separates them into trading period and non-trading period information and provides alternative evidence for the Mixture of Distribution Hypothesis (MDH). The empirical results show that the contemporary information can effectively reduce the volatility persistence; meanwhile, the lead information and the aggregate information also show some explanatory power. Some future directions are pointed out in the concluding remarks.

Suggested Citation

  • Shen, Dehua & Zhang, Wei & Xiong, Xiong & Li, Xiao & Zhang, Yongjie, 2016. "Trading and non-trading period Internet information flow and intraday return volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 519-524.
    • Handle: RePEc:eee:phsmap:v:451:y:2016:i:c:p:519-524
    DOI: 10.1016/j.physa.2016.01.086
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    References listed on IDEAS

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