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High frequency trading and the 2008 short-sale ban

Citations

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Cited by:

  1. Yang, Haijun & Xue, Feng, 2021. "Analysis of stock market volatility: Adjusted VPIN with high-frequency data," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 210-222.
  2. Kang, Jongho & Kang, Jangkoo & Kwon, Kyung Yoon, 2022. "Market versus limit orders of speculative high-frequency traders and price discovery," Research in International Business and Finance, Elsevier, vol. 63(C).
  3. Qixuan Luo & Yu Shi & Xuan Zhou & Handong Li, 2021. "Research on the Effects of Institutional Liquidation Strategies on the Market Based on Multi-agent Model," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1025-1049, December.
  4. Eaton, Gregory W. & Green, T. Clifton & Roseman, Brian S. & Wu, Yanbin, 2022. "Retail trader sophistication and stock market quality: Evidence from brokerage outages," Journal of Financial Economics, Elsevier, vol. 146(2), pages 502-528.
  5. Carè, Rosella & Cumming, Douglas, 2024. "Technology and automation in financial trading: A bibliometric review," Research in International Business and Finance, Elsevier, vol. 71(C).
  6. Xiaoman, Jin & Qing, Li & Jun, Wang & Jingmei, Zhao, 2023. "Voice or noise? Repetitive information and stock performance," Finance Research Letters, Elsevier, vol. 52(C).
  7. Jing Nie & Juliana Malagon & Julian Williams, 2022. "The impact of high speed quoting on execution risk dynamics: Evidence from interest rate futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(8), pages 1434-1465, August.
  8. Luong, Phat V. & Sopranzetti, Ben, 2022. "Commodity markets intervention: Consequences of speculation, and informed trading," Journal of Commodity Markets, Elsevier, vol. 26(C).
  9. Arumugam, Devika, 2023. "Algorithmic trading: Intraday profitability and trading behavior," Economic Modelling, Elsevier, vol. 128(C).
  10. Peter N Dixon, 2021. "Why Do Short Selling Bans Increase Adverse Selection and Decrease Price Efficiency? [The market for ‘lemons’: Quality uncertainty and the market mechanism]," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 11(1), pages 122-168.
  11. Ya‐Kai Chang & Robin K. Chou, 2022. "Algorithmic trading and market quality: Evidence from the Taiwan index futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(10), pages 1837-1855, October.
  12. Rif, Alexandru & Utz, Sebastian, 2021. "Short-term stock price reversals after extreme downward price movements," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 123-133.
  13. Hautsch, Nikolaus & Noé, Michael & Zhang, S. Sarah, 2017. "The ambivalent role of high-frequency trading in turbulent market periods," CFS Working Paper Series 580, Center for Financial Studies (CFS).
  14. Nilabhra Bhattacharya & Bidisha Chakrabarty & Xu (Frank) Wang, 2020. "High-frequency traders and price informativeness during earnings announcements," Review of Accounting Studies, Springer, vol. 25(3), pages 1156-1199, September.
  15. Chakrabarty, Bidisha & Moulton, Pamela C. & Pascual, Roberto, 2017. "Trading system upgrades and short-sale bans: Uncoupling the effects of technology and regulation," Journal of Empirical Finance, Elsevier, vol. 43(C), pages 74-90.
  16. Ravi Kashyap, 2019. "Imitation in the Imitation Game," Papers 1911.06893, arXiv.org.
  17. Nathalie Oriol & Iryna Veryzhenko, 2019. "Market structure or traders' behavior? A multi agent model to assess flash crash phenomena and their regulation," Quantitative Finance, Taylor & Francis Journals, vol. 19(7), pages 1075-1092, July.
  18. Yang, Haijun & Ge, Hengshun & Luo, Ying, 2020. "The optimal bid-ask price strategies of high-frequency trading and the effect on market liquidity," Research in International Business and Finance, Elsevier, vol. 53(C).
  19. Chen, Kejing & Jiang, Lin & Kang, Yanling & Yang, Mo & Zhen, Jiahua, 2024. "Blockholder exit threats and excess executive perks," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 80-97.
  20. Mestel, Roland & Murg, Michael & Theissen, Erik, 2018. "Algorithmic trading and liquidity: Long term evidence from Austria," Finance Research Letters, Elsevier, vol. 26(C), pages 198-203.
  21. Kemme, David M. & McInish, Thomas H. & Zhang, Jiang, 2022. "Market fairness and efficiency: Evidence from the Tokyo Stock Exchange," Journal of Banking & Finance, Elsevier, vol. 134(C).
  22. Yamani, Ehab, 2023. "Return–volume nexus in financial markets: A survey of research," Research in International Business and Finance, Elsevier, vol. 65(C).
  23. Seungho Lee, 2022. "The COVID-19 pandemic, short-sale ban, and market efficiency: empirical evidence from the European equity markets," Journal of Asset Management, Palgrave Macmillan, vol. 23(2), pages 156-171, March.
  24. repec:grz:wpsses:2018-03 is not listed on IDEAS
  25. Aït-Sahalia, Yacine & Brunetti, Celso, 2020. "High frequency traders and the price process," Journal of Econometrics, Elsevier, vol. 217(1), pages 20-45.
  26. Ekinci, Cumhur & Ersan, Oğuz, 2022. "High-frequency trading and market quality: The case of a “slightly exposed” market," International Review of Financial Analysis, Elsevier, vol. 79(C).
  27. Arumugam, Devika & Krishna Prasanna, P., 2021. "Commonality and contrarian trading among algorithmic traders," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
  28. John Coughlan & Alexei G. Orlov, 2023. "High‐frequency trading and market quality: Evidence from account‐level futures data," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(8), pages 1126-1160, August.
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