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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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    6. Senarathne Chamil W. & Šoja Tijana, 2019. "Heteroskedasticity in Excess Bitcoin Return Data: Google Trend vs. Garch Effects," Financial Sciences. Nauki o Finansach, Sciendo, vol. 24(3), pages 35-45, September.
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    13. Ying Wang & Hongwei Zhang & Wang Gao & Cai Yang, 2023. "Spillover effects from news to travel and leisure stocks during the COVID-19 pandemic: Evidence from the time and frequency domains," Tourism Economics, , vol. 29(2), pages 460-487, March.
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    16. Zuochao Zhang & Yongjie Zhang & Dehua Shen & Wei Zhang, 2018. "The Dynamic Cross-Correlations between Mass Media News, New Media News, and Stock Returns," Complexity, Hindawi, vol. 2018, pages 1-11, February.
    17. Zhang, Wei & Li, Xiao & Shen, Dehua & Teglio, Andrea, 2016. "R2 and idiosyncratic volatility: Which captures the firm-specific return variation?," Economic Modelling, Elsevier, vol. 55(C), pages 298-304.
    18. Ahadzie, Richard Mawulawoe & Jeyasreedharan, Nagaratnam, 2020. "Trading volume and realized higher-order moments in the Australian stock market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
    19. Shen, Dehua & Li, Xiao & Zhang, Wei, 2017. "Baidu news coverage and its impacts on order imbalance and large-size trade of Chinese stocks," Finance Research Letters, Elsevier, vol. 23(C), pages 210-216.
    20. Gao, Yang & Wang, Yaojun & Wang, Chao & Liu, Chao, 2018. "Internet attention and information asymmetry: Evidence from Qihoo 360 search data on the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 802-811.
    21. Dehua Shen & Yongjie Zhang & Xiong Xiong & Wei Zhang, 2017. "Baidu index and predictability of Chinese stock returns," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 3(1), pages 1-8, December.
    22. Zhao, Ruwei & Xiong, Xiong & Shen, Dehua, 2018. "Investor attention and performance of IPO firms: Evidence from online searches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 342-348.
    23. Clements, A.E. & Liao, Y., 2020. "Firm-specific information and systemic risk," Economic Modelling, Elsevier, vol. 90(C), pages 480-493.
    24. Lahmiri, Salim, 2017. "Asymmetric and persistent responses in price volatility of fertilizers through stable and unstable periods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 405-414.
    25. Zhang, Yongjie & Song, Weixin & Shen, Dehua & Zhang, Wei, 2016. "Market reaction to internet news: Information diffusion and price pressure," Economic Modelling, Elsevier, vol. 56(C), pages 43-49.

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