IDEAS home Printed from https://ideas.repec.org/a/oup/rfinst/v32y2019i12p4997-5047..html
   My bibliography  Save this article

Chasing Private Information

Author

Listed:
  • Marcin Kacperczyk
  • Emiliano S Pagnotta

Abstract

Using over 5,000 trades unequivocally based on nonpublic information about firm fundamentals, we find that asymmetric information proxies display abnormal values on days with informed trading. Volatility and volume are abnormally high, whereas illiquidity is low, in equity and option markets. Daily returns reflect the sign of private signals, but bid-ask spreads are lower when informed investors trade. Market makers’ learning under event uncertainty and limit orders help explain these findings. The cross-section of information duration indicates that traders select days with high uninformed volume. Evidence from the U.S. SEC Whistleblower Reward Program and the FINRA involvement addresses selection concerns.Received January 11, 2017; editorial decision December 17, 2018 by Editor Andrew Karolyi. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Suggested Citation

  • Marcin Kacperczyk & Emiliano S Pagnotta, 2019. "Chasing Private Information," The Review of Financial Studies, Society for Financial Studies, vol. 32(12), pages 4997-5047.
    • Handle: RePEc:oup:rfinst:v:32:y:2019:i:12:p:4997-5047.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/rfs/hhz029
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Cremers, Martijn & Weinbaum, David, 2010. "Deviations from Put-Call Parity and Stock Return Predictability," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(2), pages 335-367, April.
    2. Lee, Charles M C & Ready, Mark J, 1991. "Inferring Trade Direction from Intraday Data," Journal of Finance, American Finance Association, vol. 46(2), pages 733-746, June.
    3. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    4. Goyenko, Ruslan Y. & Holden, Craig W. & Trzcinka, Charles A., 2009. "Do liquidity measures measure liquidity?," Journal of Financial Economics, Elsevier, vol. 92(2), pages 153-181, May.
    5. Craig W. Holden & Stacey Jacobsen & Avanidhar Subrahmanyam, 2014. "The Empirical Analysis of Liquidity," Foundations and Trends(R) in Finance, now publishers, vol. 8(4), pages 263-365, December.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Nakazono, Yoshiyuki & Koga, Maiko & Sugo, Tomohiro, 2020. "Private information and analyst coverage: Evidence from firm survey data," Journal of Economic Behavior & Organization, Elsevier, vol. 174(C), pages 284-298.
    2. Roberto Riccò & Barbara Rindi & Duane J. Seppi, 2020. "Information, Liquidity, and Dynamic Limit Order Markets," Working Papers 660, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    3. Bilan, Andrada & Ongena, Steven & Pancaro, Cosimo, 2023. "Bank private information in CDS markets," Working Paper Series 2818, European Central Bank.
    4. Péter Kondor & Gábor Pintér, 2022. "Clients' Connections: Measuring the Role of Private Information in Decentralized Markets," Journal of Finance, American Finance Association, vol. 77(1), pages 505-544, February.
    5. Gilstrap, Collin & Petkevich, Alex & Teterin, Pavel, 2020. "Striking up with the in crowd: When option markets and insiders agree," Journal of Banking & Finance, Elsevier, vol. 120(C).
    6. Akey, Pat & Grégoire, Vincent & Martineau, Charles, 2022. "Price revelation from insider trading: Evidence from hacked earnings news," Journal of Financial Economics, Elsevier, vol. 143(3), pages 1162-1184.
    7. Betzer, André & Gider, Jasmin & Limbach, Peter, 2022. "Do financial advisors matter for M&A pre-announcement returns?," CFR Working Papers 22-03, University of Cologne, Centre for Financial Research (CFR).
    8. Akey, Pat & Grégoire, Vincent & Martineau, Charles, 2021. "Price Revelation from Insider Trading: Evidence from Hacked Earnings News," SocArXiv qe6tu, Center for Open Science.
    9. Contreras, Harold & Korczak, Adriana & Korczak, Piotr, 2023. "Religion and insider trading profits," Journal of Banking & Finance, Elsevier, vol. 149(C).
    10. Park, Yang-Ho, 2022. "Informed trading in foreign exchange futures: Payroll news timing," Journal of Banking & Finance, Elsevier, vol. 135(C).
    11. Brolley, Michael & Malinova, Katya, 2021. "Informed liquidity provision in a limit order market," Journal of Financial Markets, Elsevier, vol. 52(C).
    12. Mengyu Zhang & Thanos Verousis & Iordanis Kalaitzoglou, 2022. "Information and the arrival rate of option trading volume," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(4), pages 605-644, April.
    13. Ping-Chen Tsai & Chi-Ming Tsai, 2021. "Estimating the proportion of informed and speculative traders in financial markets: evidence from exchange rate," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(3), pages 443-470, July.
    14. Patel, Vinay & Putniņš, Tālis J. & Michayluk, David & Foley, Sean, 2020. "Price discovery in stock and options markets," Journal of Financial Markets, Elsevier, vol. 47(C).
    15. James, Robert & Leung, Henry & Prokhorov, Artem, 2023. "A machine learning attack on illegal trading," Journal of Banking & Finance, Elsevier, vol. 148(C).
    16. Joel Peress & Daniel Schmidt, 2020. "Glued to the TV: Distracted Noise Traders and Stock Market Liquidity," Journal of Finance, American Finance Association, vol. 75(2), pages 1083-1133, April.
    17. Goldman, Nathan C. & Ozel, Naim Bugra, 2023. "Executive compensation, individual-level tax rates, and insider trading profits," Journal of Accounting and Economics, Elsevier, vol. 76(1).
    18. Patrick Augustin & Menachem Brenner & Marti G. Subrahmanyam, 2019. "Informed Options Trading Prior to Takeover Announcements: Insider Trading?," Management Science, INFORMS, vol. 65(12), pages 5697-5720, December.
    19. Corey Garriot & Ryan Riordan, 2020. "Trading on Long-term Information," Staff Working Papers 20-20, Bank of Canada.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Emiliano Pagnotta, 2016. "Chasing Private Information," 2016 Meeting Papers 1673, Society for Economic Dynamics.
    2. Lof, Matthijs & van Bommel, Jos, 2023. "Asymmetric information and the distribution of trading volume," Journal of Corporate Finance, Elsevier, vol. 82(C).
    3. Jon Kerr & Gil Sadka & Ronnie Sadka, 2020. "Illiquidity and Price Informativeness," Management Science, INFORMS, vol. 66(1), pages 334-351, January.
    4. Fricke, Christoph & Menkhoff, Lukas, 2014. "Financial conditions, macroeconomic factors and (un)expected bond excess returns," Discussion Papers 35/2014, Deutsche Bundesbank.
    5. Chen, Jiayuan & Gong, Di & Muckley, Cal, 2020. "Stock market illiquidity, bargaining power and the cost of borrowing," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 181-206.
    6. Hagströmer, Björn, 2021. "Bias in the effective bid-ask spread," Journal of Financial Economics, Elsevier, vol. 142(1), pages 314-337.
    7. Nyborg, Kjell & Wang, Zexi, 2019. "Corporate cash holdings: Stock liquidity and the repurchase motive," CEPR Discussion Papers 13791, C.E.P.R. Discussion Papers.
    8. Zeynep Cobandag Guloglu & Cumhur Ekinci, 2022. "Liquidity measurement: A comparative review of the literature with a focus on high frequency," Journal of Economic Surveys, Wiley Blackwell, vol. 36(1), pages 41-74, February.
    9. Simon Hagemann & Christoph Weber, 2013. "An Empirical Analysis of Liquidity and its Determinants in The German Intraday Market for Electricity," EWL Working Papers 1317, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Oct 2013.
    10. Huh, Sahn-Wook, 2014. "Price impact and asset pricing," Journal of Financial Markets, Elsevier, vol. 19(C), pages 1-38.
    11. Yildiz, Serhat & Van Ness, Bonnie & Van Ness, Robert, 2020. "VPIN, liquidity, and return volatility in the U.S. equity markets," Global Finance Journal, Elsevier, vol. 45(C).
    12. Nyborg, Kjell & Wang, Zexi, 2013. "Stock Liquidity and Corporate Cash Holdings," CEPR Discussion Papers 9535, C.E.P.R. Discussion Papers.
    13. Vayanos, Dimitri & Wang, Jiang, 2013. "Market Liquidity—Theory and Empirical Evidence ," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1289-1361, Elsevier.
    14. Blankespoor, Elizabeth & deHaan, Ed & Marinovic, Iván, 2020. "Disclosure processing costs, investors’ information choice, and equity market outcomes: A review," Journal of Accounting and Economics, Elsevier, vol. 70(2).
    15. Lei, Xiaoyan & Zhou, Yuegang & Zhu, Xiaoneng, 2013. "Capital gains, illiquidity, and stock returns," Pacific-Basin Finance Journal, Elsevier, vol. 25(C), pages 273-293.
    16. Marshall, Ben R. & Nguyen, Nhut H. & Visaltanachoti, Nuttawat, 2018. "Do liquidity proxies measure liquidity accurately in ETFs?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 94-111.
    17. Fricke, Christoph & Menkhoff, Lukas, 2015. "Financial conditions, macroeconomic factors and disaggregated bond excess returns," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 80-94.
    18. Nina Karnaukh & Angelo Ranaldo & Paul Söderlind, 2015. "Understanding FX Liquidity," Review of Financial Studies, Society for Financial Studies, vol. 28(11), pages 3073-3108.
    19. Thomas Johann & Erik Theissen, 2013. "Liquidity measures," Chapters, in: Adrian R. Bell & Chris Brooks & Marcel Prokopczuk (ed.), Handbook of Research Methods and Applications in Empirical Finance, chapter 10, pages 238-255, Edward Elgar Publishing.
    20. Lim, Kian-Ping & Thian, Tze-Chung & Hooy, Chee-Wooi, 2015. "Corporate Shareholdings and the Liquidity of Malaysian Stocks: Investor Heterogeneity, Trading Account Types and the Underlying Channels," MPRA Paper 67602, University Library of Munich, Germany.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:oup:rfinst:v:32:y:2019:i:12:p:4997-5047.. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Oxford University Press (email available below). General contact details of provider: https://edirc.repec.org/data/sfsssea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.