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Baidu news coverage and its impacts on order imbalance and large-size trade of Chinese stocks

Citations

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Cited by:

  1. Anwer, Zaheer & Khan, Muhammad Arif & Hassan, M. Kabir & Singh, Manjeet Kaur Harnek, 2024. "Assessing dynamic co-movement of news based uncertainty indices and distance-to -default of global FinTech firms," Research in International Business and Finance, Elsevier, vol. 71(C).
  2. Yousaf, Imran & Youssef, Manel & Goodell, John W., 2022. "Quantile connectedness between sentiment and financial markets: Evidence from the S&P 500 twitter sentiment index," International Review of Financial Analysis, Elsevier, vol. 83(C).
  3. Zhang, Wei & Wang, Pengfei & Li, Xiao & Shen, Dehua, 2018. "Twitter’s daily happiness sentiment and international stock returns: Evidence from linear and nonlinear causality tests," Journal of Behavioral and Experimental Finance, Elsevier, vol. 18(C), pages 50-53.
  4. Shen, Dehua & Li, Xiao & Zhang, Wei, 2018. "Baidu news information flow and return volatility: Evidence for the Sequential Information Arrival Hypothesis," Economic Modelling, Elsevier, vol. 69(C), pages 127-133.
  5. Yingtong Chen & Fei Wu & Dayong Zhang & Qiang Ji, 2024. "Tourism in pandemic: the role of digital travel vouchers in China," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
  6. Zhao, Ruwei, 2020. "Quantifying the cross sectional relation of daily happiness sentiment and return skewness: Evidence from US industries," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
  7. Wan, Daoxia & Xue, Rui & Linnenluecke, Martina & Tian, Jinfang & Shan, Yuli, 2021. "The impact of investor attention during COVID-19 on investment in clean energy versus fossil fuel firms," Finance Research Letters, Elsevier, vol. 43(C).
  8. Zhao, Ruwei, 2020. "Quantifying the cross sectional relation of daily happiness sentiment and stock return: Evidence from US," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).
  9. Ruwei Zhao & Xiong Xiong & Junjun Ma & Yuzhao Zhang & Yongjie Zhang, 2025. "Baidu News and the return volatility of Chinese commodity futures: evidence for the sequential information arrival hypothesis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-24, December.
  10. Zhang, Zuochao & Shen, Dehua, 2024. "Not all the news fitting to reprint: Evidence from price-volume relationship," Finance Research Letters, Elsevier, vol. 62(PA).
  11. Zhao, Ruwei, 2020. "Quantifying the correlation of media coverage and stock price crash risk: A panel study from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
  12. Gang Chu & John W. Goodell & Xiao Li & Yongjie Zhang, 2023. "Understanding short‐term price pressure from index reconstitutions: Evidence from the CSI 300," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(2), pages 2421-2440, June.
  13. Chou, Ke-Hsin & Day, Min-Yuh & Chiu, Chien-Liang, 2023. "Do bitcoin news information flow and return volatility fit the sequential information arrival hypothesis and the mixture of distribution hypothesis?," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 365-385.
  14. Jianchun Fang & Wanshan Wu & Zhou Lu & Eunho Cho, 2019. "Using Baidu Index To Nowcast Mobile Phone Sales In China," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 64(01), pages 83-96, March.
  15. Naeem, Muhammad Abubakr & Farid, Saqib & Faruk, Balli & Shahzad, Syed Jawad Hussain, 2020. "Can happiness predict future volatility in stock markets?," Research in International Business and Finance, Elsevier, vol. 54(C).
  16. Feng, Wenjun & Wang, Yiming & Zhang, Zhengjun, 2018. "Informed trading in the Bitcoin market," Finance Research Letters, Elsevier, vol. 26(C), pages 63-70.
  17. Wei, Kai & Zhang, Zuopeng Justin & Lin, Boqiang, 2024. "Does news propaganda really affect residents’ electricity rebound effect: New evidence of non-price information," Energy, Elsevier, vol. 300(C).
  18. Zhang, Zuochao & Shen, Dehua, 2024. "Internet stock message boards and the price–volume relationship: Registered users vs non-registered users," Finance Research Letters, Elsevier, vol. 61(C).
  19. Zhang, Ting & Gu, Gao-Feng & Zhou, Wei-Xing, 2019. "Order imbalances and market efficiency: New evidence from the Chinese stock market," Emerging Markets Review, Elsevier, vol. 38(C), pages 458-467.
  20. 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.
  21. Ma, Yaming & Duan, Qiqi & Wu, Hanhong, 2021. "Does a stock's name affect its return? Evidence from the Chinese stock market during the China–US trade conflict," Finance Research Letters, Elsevier, vol. 40(C).
  22. Li, Xiao & Shen, Dehua & Zhang, Wei, 2018. "Do Chinese internet stock message boards convey firm-specific information?," Pacific-Basin Finance Journal, Elsevier, vol. 49(C), pages 1-14.
  23. 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.
  24. Ekinci, Cumhur & Akyildirim, Erdinc & Corbet, Shaen, 2019. "Analysing the dynamic influence of US macroeconomic news releases on Turkish stock markets," Finance Research Letters, Elsevier, vol. 31(C), pages 155-164.
  25. Kao, Yu-Sheng & Day, Min-Yuh & Chou, Ke-Hsin, 2024. "A comparison of bitcoin futures return and return volatility based on news sentiment contemporaneously or lead-lag," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
  26. Yongjie Zhang & Yue Li & Dehua Shen, 2022. "Investor Attention and the Carbon Emission Markets in China: A Nonparametric Wavelet-Based Causality Test," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 29(1), pages 123-137, March.
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