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Discerning information from trade data

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Cited by:

  1. Cipriani, Marco & Guarino, Antonio & Uthemann, Andreas, 2022. "Financial transaction taxes and the informational efficiency of financial markets: A structural estimation," Journal of Financial Economics, Elsevier, vol. 146(3), pages 1044-1072.
  2. Klova, Valeriia & Odegaard, Bernt Arne, 2018. "Equity trading costs have fallen less than commonly thought. Evidence using alternative trading cost estimators," UiS Working Papers in Economics and Finance 2018/4, University of Stavanger, revised 2019.
  3. Rosati, Pierangelo & Cummins, Mark & Deeney, Peter & Gogolin, Fabian & van der Werff, Lisa & Lynn, Theo, 2017. "The effect of data breach announcements beyond the stock price: Empirical evidence on market activity," International Review of Financial Analysis, Elsevier, vol. 49(C), pages 146-154.
  4. Huang, Hong-Gia & Tsai, Wei-Che & Weng, Pei-Shih & Wu, Ming-Hung, 2021. "Volatility of order imbalance of institutional traders and expected asset returns: Evidence from Taiwan," Journal of Financial Markets, Elsevier, vol. 52(C).
  5. repec:uts:finphd:39 is not listed on IDEAS
  6. Chen, Tao, 2018. "Round-number biases and informed trading in global markets," Journal of Business Research, Elsevier, vol. 92(C), pages 105-117.
  7. 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.
  8. Kara Karpman & Sumanta Basu & David Easley, 2022. "Learning Financial Networks with High-frequency Trade Data," Papers 2208.03568, arXiv.org.
  9. Vincent Van Kervel & Albert J. Menkveld, 2019. "High‐Frequency Trading around Large Institutional Orders," Journal of Finance, American Finance Association, vol. 74(3), pages 1091-1137, June.
  10. Chen, Shi & Härdle, Wolfgang & Schienle, Melanie, 2021. "High-dimensional statistical learning techniques for time-varying limit order book networks," IRTG 1792 Discussion Papers 2021-015, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  11. Yergeau, Gabriel, 2016. "Profitability and Market Quality of High Frequency Market-makers: An Empirical Investigation," Working Papers 16-3, HEC Montreal, Canada Research Chair in Risk Management.
  12. Yan Han & Xue-Feng Shao & Xin Cui & Xiao-Guang Yue & Kelvin Joseph Bwalya & Otilia Manta, 2019. "Assessing Investor Belief: An Analysis of Trading for Sustainable Growth of Stock Markets," Sustainability, MDPI, vol. 11(20), pages 1-18, October.
  13. Donglian Ma & Pengxiang Zhai, 2021. "The Accuracy of the Tick Rule in the Bitcoin Market," SAGE Open, , vol. 11(2), pages 21582440211, May.
  14. Allen Carrion & Madhuparna Kolay, 2020. "Trade signing in fast markets," The Financial Review, Eastern Finance Association, vol. 55(3), pages 385-404, August.
  15. Abad, David & Massot, Magdalena & Pascual, Roberto, 2018. "Evaluating VPIN as a trigger for single-stock circuit breakers," Journal of Banking & Finance, Elsevier, vol. 86(C), pages 21-36.
  16. Jangkoo Kang & Kyung Yoon Kwon & Wooyeon Kim, 2020. "Flow toxicity of high‐frequency trading and its impact on price volatility: Evidence from the KOSPI 200 futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(2), pages 164-191, February.
  17. Xingguo Luo & Xiaoli Yu & Shihua Qin & Qi Xu, 2020. "Option trading and the cross‐listed stock returns: Evidence from Chinese A–H shares," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(11), pages 1665-1690, November.
  18. Onur, Esen & Roberts, John S. & Tuzun, Tugkan, 2023. "Trader positions and aggregate portfolio demand," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
  19. Ioane Muni Toke, 2016. "Reconstruction of Order Flows using Aggregated Data," Papers 1604.02759, arXiv.org.
  20. Marc J. M. Bohmann & Vinay Patel, 2022. "Informed options trading prior to FDA announcements," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 49(7-8), pages 1211-1236, July.
  21. David Easley & Marcos López de Prado & Maureen O’Hara & Zhibai Zhang & Wei Jiang, 2021. "Microstructure in the Machine Age [The risk of machine learning]," The Review of Financial Studies, Society for Financial Studies, vol. 34(7), pages 3316-3363.
  22. Kaul, Aditya & Kayacetin, Nuri Volkan, 2017. "Flight-to-quality, economic fundamentals, and stock returns," Journal of Banking & Finance, Elsevier, vol. 80(C), pages 162-175.
  23. PeiLin Hsieh & QinQin Zhang & Yajun Wang, 2018. "Jump risk and option liquidity in an incomplete market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(11), pages 1334-1369, November.
  24. Mark Fedenia & Tavy Ronen & Seunghan Nam, 2024. "Machine learning and trade direction classification: insights from the corporate bond market," Review of Quantitative Finance and Accounting, Springer, vol. 63(1), pages 1-36, July.
  25. Chiranjit Dutta & Kara Karpman & Sumanta Basu & Nalini Ravishanker, 2023. "Review of Statistical Approaches for Modeling High-Frequency Trading Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 1-48, May.
  26. Jurkatis, Simon, 2022. "Inferring trade directions in fast markets," Journal of Financial Markets, Elsevier, vol. 58(C).
  27. Nguyet Nguyen, 2022. "Informed Trading in Dark Pools: Fair-Access Dark Venue vs. Restricted-Access Dark Venues," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 12(02), pages 1-37, June.
  28. Fei Su, 2018. "Essays on Price Discovery and Volatility Dynamics in the Foreign Exchange Market," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2018, January-A.
  29. Acheson, Graeme G. & Coyle, Christopher & Turner, John D., 2018. "Prices and informed trading: Evidence from an early stock market," QUCEH Working Paper Series 2018-05, Queen's University Belfast, Queen's University Centre for Economic History.
  30. Jia, Yuecheng & Wu, Yangru & Yan, Shu & Liu, Yuzheng, 2023. "A seesaw effect in the cryptocurrency market: Understanding the return cross predictability of cryptocurrencies," Journal of Empirical Finance, Elsevier, vol. 74(C).
  31. Borochin, Paul & Rush, Stephen, 2022. "Information networks in the financial sector and systemic risk," Journal of Banking & Finance, Elsevier, vol. 134(C).
  32. Lunawat, Radhika, 2021. "Learning from trading activity in laboratory security markets with higher-order uncertainty," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 90(C).
  33. repec:uts:finphd:38 is not listed on IDEAS
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