IDEAS home Printed from https://ideas.repec.org/a/spr/jeicoo/v16y2021i3d10.1007_s11403-020-00308-z.html
   My bibliography  Save this article

Estimating the proportion of informed and speculative traders in financial markets: evidence from exchange rate

Author

Listed:
  • Ping-Chen Tsai

    (National Sun Yat-sen University)

  • Chi-Ming Tsai

    (Southern Taiwan University of Science and Technology)

Abstract

We study the Glosten–Milgrom model and estimate the proportion of informed traders or speculators using bid–ask spread and price range. The GM model is generalized in terms of a key parameter $$ \theta $$ θ —the probability of making a correct decision by an agent. Informed traders have $$ \theta = 1 $$ θ = 1 , and uninformed traders have $$ \theta = 1/2 $$ θ = 1 / 2 in the GM model. Speculators are defined to be agents with $$ 1/2 1/2 $$ θ ¯ > 1 / 2 using simple trading rules within short trading horizons and net of transaction cost.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:jeicoo:v:16:y:2021:i:3:d:10.1007_s11403-020-00308-z
    DOI: 10.1007/s11403-020-00308-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11403-020-00308-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11403-020-00308-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    References listed on IDEAS

    as
    1. Duarte, Jefferson & Young, Lance, 2009. "Why is PIN priced?," Journal of Financial Economics, Elsevier, vol. 91(2), pages 119-138, February.
    2. Daniel Preve & Yiu‐Kuen Tse, 2013. "Estimation Of Time‐Varying Adjusted Probability Of Informed Trading And Probability Of Symmetric Order‐Flow Shock," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(7), pages 1138-1152, November.
    3. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    4. Vitale, Paolo, 2000. "Speculative noise trading and manipulation in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 19(5), pages 689-712, October.
    5. Avery, Christopher & Zemsky, Peter, 1998. "Multidimensional Uncertainty and Herd Behavior in Financial Markets," American Economic Review, American Economic Association, vol. 88(4), pages 724-748, September.
    6. Peng, Lin, 2005. "Learning with Information Capacity Constraints," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 40(2), pages 307-329, June.
    7. Krista Schwarz, 2012. "Are speculators informed?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 32(1), pages 1-23, January.
    8. Gao, Feng & Song, Fengming & Wang, Jun, 2013. "Rational expectations equilibrium with uncertain proportion of informed traders," Journal of Financial Markets, Elsevier, vol. 16(3), pages 387-413.
    9. Madrigal, Vicente, 1996. "Non-fundamental Speculation," Journal of Finance, American Finance Association, vol. 51(2), pages 553-578, June.
    10. Marcin Kacperczyk & Emiliano S Pagnotta, 2019. "Chasing Private Information," Review of Financial Studies, Society for Financial Studies, vol. 32(12), pages 4997-5047.
    11. Lei, Qin & Wu, Guojun, 2005. "Time-varying informed and uninformed trading activities," Journal of Financial Markets, Elsevier, vol. 8(2), pages 153-181, May.
    12. Glosten, Lawrence R. & Milgrom, Paul R., 1985. "Bid, ask and transaction prices in a specialist market with heterogeneously informed traders," Journal of Financial Economics, Elsevier, vol. 14(1), pages 71-100, March.
    13. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    14. Banerjee, Snehal & Green, Brett, 2015. "Signal or noise? Uncertainty and learning about whether other traders are informed," Journal of Financial Economics, Elsevier, vol. 117(2), pages 398-423.
    15. David Easley & Robert F. Engle & Maureen O'Hara & Liuren Wu, 2008. "Time-Varying Arrival Rates of Informed and Uninformed Trades," Journal of Financial Econometrics, Oxford University Press, vol. 6(2), pages 171-207, Spring.
    16. Michael J. Brennan & Sahn-Wook Huh & Avanidhar Subrahmanyam, 2018. "High-Frequency Measures of Informed Trading and Corporate Announcements," Review of Financial Studies, Society for Financial Studies, vol. 31(6), pages 2326-2376.
    17. 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.
    18. Huang, Roger D & Stoll, Hans R, 1997. "The Components of the Bid-Ask Spread: A General Approach," Review of Financial Studies, Society for Financial Studies, vol. 10(4), pages 995-1034.
    19. Easley, David & Kiefer, Nicholas M & O'Hara, Maureen, 1997. "One Day in the Life of a Very Common Stock," Review of Financial Studies, Society for Financial Studies, vol. 10(3), pages 805-835.
    20. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    21. Craig Burnside & Martin Eichenbaum & Sergio Rebelo, 2009. "Understanding the Forward Premium Puzzle: A Microstructure Approach," American Economic Journal: Macroeconomics, American Economic Association, vol. 1(2), pages 127-154, July.
    22. Pong, Shiuyan & Shackleton, Mark B. & Taylor, Stephen J. & Xu, Xinzhong, 2004. "Forecasting currency volatility: A comparison of implied volatilities and AR(FI)MA models," Journal of Banking & Finance, Elsevier, vol. 28(10), pages 2541-2563, October.
    23. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
    24. Brandt, Michael W. & Jones, Christopher S., 2006. "Volatility Forecasting With Range-Based EGARCH Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 470-486, October.
    25. Xiangkang Yin & Jing Zhao, 2015. "A Hidden Markov Model Approach to Information‐Based Trading: Theory and Applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(7), pages 1210-1234, November.
    26. Easley, David & O'Hara, Maureen, 1987. "Price, trade size, and information in securities markets," Journal of Financial Economics, Elsevier, vol. 19(1), pages 69-90, September.
    27. Kerry Back & Kevin Crotty & Tao Li, 2018. "Identifying Information Asymmetry in Securities Markets," Review of Financial Studies, Society for Financial Studies, vol. 31(6), pages 2277-2325.
    28. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    29. Marmora, Paul & Rytchkov, Oleg, 2018. "Learning about noise," Journal of Banking & Finance, Elsevier, vol. 89(C), pages 209-224.
    30. Anthony Tay & Christopher Ting & Yiu Kuen Tse & Mitch Warachka, 2009. "Using High-Frequency Transaction Data to Estimate the Probability of Informed Trading," Journal of Financial Econometrics, Oxford University Press, vol. 7(3), pages 288-311, Summer.
    31. Ken Nyholm, 2002. "Estimating the Probability of Informed Trading," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 25(4), pages 485-505, December.
    32. Basu, Kaushik & Varoudakis, Aristomene, 2013. "How to move the exchange rate if you must: the diverse practice of foreign exchange intervention by central banks and a proposal for doing it better," Policy Research Working Paper Series 6460, The World Bank.
    33. David Easley & Marcos M. López de Prado & Maureen O'Hara, 2012. "Flow Toxicity and Liquidity in a High-frequency World," Review of Financial Studies, Society for Financial Studies, vol. 25(5), pages 1457-1493.
    34. Easley, David, et al, 1996. "Liquidity, Information, and Infrequently Traded Stocks," Journal of Finance, American Finance Association, vol. 51(4), pages 1405-1436, September.
    35. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    36. Chang, Sanders S. & Chang, Lenisa V. & Wang, F. Albert, 2014. "A dynamic intraday measure of the probability of informed trading and firm-specific return variation," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 80-94.
    37. Chou, Ray Yeutien, 2005. "Forecasting Financial Volatilities with Extreme Values: The Conditional Autoregressive Range (CARR) Model," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 561-582, June.
    38. Easley, David & O'Hara, Maureen, 1992. "Time and the Process of Security Price Adjustment," Journal of Finance, American Finance Association, vol. 47(2), pages 576-605, June.
    39. Lukáš Pichl & Cheoljun Eom & Enrico Scalas & Taisei Kaizoji (ed.), 2020. "Advanced Studies of Financial Technologies and Cryptocurrency Markets," Springer Books, Springer, number 978-981-15-4498-9, November.
    40. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, 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. Chien-Yuan Lai & Zhen-Yu Lin & Cheoljun Eom & Ping-Chen Tsai, 2022. "Market Intraday Momentum with New Measures for Trading Cost: Evidence from KOSPI Index," JRFM, MDPI, vol. 15(11), pages 1-12, November.

    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. 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.
    2. Lof, Matthijs & van Bommel, Jos, 2023. "Asymmetric information and the distribution of trading volume," Journal of Corporate Finance, Elsevier, vol. 82(C).
    3. Duarte, Jefferson & Hu, Edwin & Young, Lance, 2020. "A comparison of some structural models of private information arrival," Journal of Financial Economics, Elsevier, vol. 135(3), pages 795-815.
    4. Chang, Sanders S. & Chang, Lenisa V. & Wang, F. Albert, 2014. "A dynamic intraday measure of the probability of informed trading and firm-specific return variation," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 80-94.
    5. 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.
    6. Chang, Sanders S. & Wang, F. Albert, 2015. "Adverse selection and the presence of informed trading," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 19-33.
    7. Mazza, Paolo, 2015. "Price dynamics and market liquidity: An intraday event study on Euronext," The Quarterly Review of Economics and Finance, Elsevier, vol. 56(C), pages 139-153.
    8. 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.
    9. 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.
    10. Pérez-Rodríguez, Jorge V. & Sosvilla-Rivero, Simón & Andrada-Felix, Julián & Gómez-Déniz, Emilio, 2022. "Searching for informed traders in stock markets: The case of Banco Popular," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
    11. Travis L. Johnson & Eric C. So, 2018. "A Simple Multimarket Measure of Information Asymmetry," Management Science, INFORMS, vol. 64(3), pages 1055-1080, March.
    12. Lof, Matthijs & Bommel, Jos van, 2018. "Asymmetric information and the distribution of trading volume," Research Discussion Papers 1, Bank of Finland.
    13. repec:zbw:bofrdp:001 is not listed on IDEAS
    14. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    15. Bardong, Florian & Bartram, Söhnke M. & Yadav, Pradeep K., 2005. "Informed Trading, Information Asymmetry and Pricing of Information Risk: Empirical Evidence from the NYSE," MPRA Paper 13586, University Library of Munich, Germany, revised 10 Oct 2008.
    16. repec:zbw:bofrdp:2018_001 is not listed on IDEAS
    17. Magdalena Osinska & Andrzej Dobrzynski & Yochanan Shachmurove, 2016. "Performance Of American And Russian Joint Stock Companies On Financial Market. A Microstructure Perspective," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 11(4), pages 819-851, December.
    18. 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).
    19. 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.
    20. Lei, Qin & Wu, Guojun, 2005. "Time-varying informed and uninformed trading activities," Journal of Financial Markets, Elsevier, vol. 8(2), pages 153-181, May.
    21. Cosmin Octavian Cepoi & Filip Mihai Toma, 2016. "Estimating Probability of Informed Trading on the Bucharest Stock Exchange," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(2), pages 140-160, April.
    22. 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).

    More about this item

    Keywords

    Bid–ask spread; Asymmetric information; Speculator; Range; Market microstructure;
    All these keywords.

    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:spr:jeicoo:v:16:y:2021:i:3:d:10.1007_s11403-020-00308-z. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.