IDEAS home Printed from https://ideas.repec.org/r/eee/jbfina/v36y2012i2p454-467.html
   My bibliography  Save this item

An improved estimation method and empirical properties of the probability of informed trading

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Kitamura, Yoshihiro, 2016. "The probability of informed trading measured with price impact, price reversal, and volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 42(C), pages 77-90.
  2. Ersan, Oguz & Alıcı, Aslı, 2016. "An unbiased computation methodology for estimating the probability of informed trading (PIN)," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 43(C), pages 74-94.
  3. Emily Lin & Chu-Lan Michael Kao & Natasha Sonia Adityarini, 2021. "Data-driven tree structure for PIN models," Review of Quantitative Finance and Accounting, Springer, vol. 57(2), pages 411-427, August.
  4. Pham, Son Duy & Nguyen, Thao Thac Thanh & Do, Hung Xuan, 2022. "Effect of futures trading on the liquidity of underlying stocks: Evidence from Vietnam," Pacific-Basin Finance Journal, Elsevier, vol. 73(C).
  5. Sankaraguruswamy, Srinivasan & Shen, Jianfeng & Yamada, Takeshi, 2013. "The relationship between the frequency of news release and the information asymmetry: The role of uninformed trading," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4134-4143.
  6. Carl Chiarella & Xue-Zhong He & Lijian Wei, 2013. "Learning and Evolution of Trading Strategies in Limit Order Markets," Research Paper Series 335, Quantitative Finance Research Centre, University of Technology, Sydney.
  7. Chiarella, Carl & He, Xue-Zhong & Wei, Lijian, 2015. "Learning, information processing and order submission in limit order markets," Journal of Economic Dynamics and Control, Elsevier, vol. 61(C), pages 245-268.
  8. Ormos, Mihály & Timotity, Dusán, 2016. "Market microstructure during financial crisis: Dynamics of informed and heuristic-driven trading," Finance Research Letters, Elsevier, vol. 19(C), pages 60-66.
  9. Griffin, Jim & Oberoi, Jaideep & Oduro, Samuel D., 2021. "Estimating the probability of informed trading: A Bayesian approach," Journal of Banking & Finance, Elsevier, vol. 125(C).
  10. Jackson, David, 2013. "Estimating PIN for firms with high levels of trading," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 116-120.
  11. David Abad & Juan P. Sánchez-Ballesta & José Yagüe, 2017. "Audit opinions and information asymmetry in the stock market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 57(2), pages 565-595, June.
  12. Agudelo, Diego A. & Giraldo, Santiago & Villarraga, Edwin, 2015. "Does PIN measure information? Informed trading effects on returns and liquidity in six emerging markets," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 149-161.
  13. Thomas Pöppe & Michael Aitken & Dirk Schiereck & Ingo Wiegand, 2016. "A PIN per day shows what news convey: the intraday probability of informed trading," Review of Quantitative Finance and Accounting, Springer, vol. 47(4), pages 1187-1220, November.
  14. Tiniç, Murat & Savaser, Tanseli, 2020. "Political turmoil and the impact of foreign orders on equity prices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
  15. Chen, Yifan & Zhao, Huainan, 2012. "Informed trading, information uncertainty, and price momentum," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2095-2109.
  16. repec:zbw:bofrdp:2018_001 is not listed on IDEAS
  17. Lof, Matthijs & Bommel, Jos van, 2018. "Asymmetric information and the distribution of trading volume," Research Discussion Papers 1/2018, Bank of Finland.
  18. Kim, Sangwan & Lim, Steve C., 2017. "Earnings comparability and informed trading," Finance Research Letters, Elsevier, vol. 20(C), pages 130-136.
  19. Schreder, Max, 2018. "Idiosyncratic information and the cost of equity capital: A meta-analytic review of the literature," Journal of Accounting Literature, Elsevier, vol. 41(C), pages 142-172.
  20. Hung, Chiayu & Lai, Hung-Neng, 2022. "Information asymmetry and the profitability of technical analysis," Journal of Banking & Finance, Elsevier, vol. 134(C).
  21. Lof, Matthijs & van Bommel, Jos, 2023. "Asymmetric information and the distribution of trading volume," Journal of Corporate Finance, Elsevier, vol. 82(C).
  22. Lijian Wei & Xiong Xiong & Wei Zhang & Xue-Zhong He & Yongjie Zhang, 2017. "The effect of genetic algorithm learning with a classifier system in limit order markets," Published Paper Series 2017-3, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
  23. Malinova, Katya & Park, Andreas, 2014. "The impact of competition and information on intraday trading," Journal of Banking & Finance, Elsevier, vol. 44(C), pages 55-71.
  24. Chu-Lan Michael Kao & Emily Lin, 2023. "A new PIN model with application of the change-point detection method," Review of Quantitative Finance and Accounting, Springer, vol. 61(4), pages 1513-1528, November.
  25. Jian Wang & Yanhuang Huang & Hongrui Feng & Xingjian Li & Shu Yan, 2023. "CEO incentive compensation and stock price momentum," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(S1), pages 975-1028, April.
  26. Yan, Yuxing & Zhang, Shaojun, 2014. "Quality of PIN estimates and the PIN-return relationship," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 137-149.
  27. Petchey, James & Wee, Marvin & Yang, Joey, 2016. "Pinning down an effective measure for probability of informed trading," Pacific-Basin Finance Journal, Elsevier, vol. 40(PB), pages 456-475.
  28. Michael J. Brennan & Sahn-Wook Huh & Avanidhar Subrahmanyam, 2016. "Asymmetric Effects of Informed Trading on the Cost of Equity Capital," Management Science, INFORMS, vol. 62(9), pages 2460-2480, September.
  29. Moonsoo Kang & Kiseok Nam, 2015. "Informed trade and idiosyncratic return variation," Review of Quantitative Finance and Accounting, Springer, vol. 44(3), pages 551-572, April.
  30. David Abad & M. Fuensanta Cutillas†Gomariz & Juan Pedro Sánchez†Ballesta & José Yagüe, 2018. "Does IFRS Mandatory Adoption Affect Information Asymmetry in the Stock Market?," Australian Accounting Review, CPA Australia, vol. 28(1), pages 61-78, March.
  31. Guangchuan Li & Lei Lu & Bo Wu & Zhou Zhang, 2014. "Asymmetric information, illiquidity and asset returns: evidence from China," Quantitative Finance, Taylor & Francis Journals, vol. 14(6), pages 947-957, June.
  32. repec:zbw:bofrdp:001 is not listed on IDEAS
  33. Huh, Sahn-Wook & Lin, Hao & Mello, Antonio S., 2015. "Options market makers׳ hedging and informed trading: Theory and evidence," Journal of Financial Markets, Elsevier, vol. 23(C), pages 26-58.
  34. Arifovic, Jasmina & He, Xue-zhong & Wei, Lijian, 2022. "Machine learning and speed in high-frequency trading," Journal of Economic Dynamics and Control, Elsevier, vol. 139(C).
  35. Quan Gan & Wang Chun Wei & David Johnstone, 2015. "A faster estimation method for the probability of informed trading using hierarchical agglomerative clustering," Quantitative Finance, Taylor & Francis Journals, vol. 15(11), pages 1805-1821, November.
  36. Cosmin Octavian Cepoi & Victor Dragotă & Ruxandra Trifan & Andreea Iordache, 2023. "Probability of informed trading during the COVID-19 pandemic: the case of the Romanian stock market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-27, December.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.