IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0026705.html
   My bibliography  Save this article

Tracking Traders' Understanding of the Market Using e-Communication Data

Author

Listed:
  • Serguei Saavedra
  • Jordi Duch
  • Brian Uzzi

Abstract

Tracking the volume of keywords in Internet searches, message boards, or Tweets has provided an alternative for following or predicting associations between popular interest or disease incidences. Here, we extend that research by examining the role of e-communications among day traders and their collective understanding of the market. Our study introduces a general method that focuses on bundles of words that behave differently from daily communication routines, and uses original data covering the content of instant messages among all day traders at a trading firm over a 40-month period. Analyses show that two word bundles convey traders' understanding of same day market events and potential next day market events. We find that when market volatility is high, traders' communications are dominated by same day events, and when volatility is low, communications are dominated by next day events. We show that the stronger the traders' attention to either same day or next day events, the higher their collective trading performance. We conclude that e-communication among traders is a product of mass collaboration over diverse viewpoints that embodies unique information about their weak or strong understanding of the market.

Suggested Citation

  • Serguei Saavedra & Jordi Duch & Brian Uzzi, 2011. "Tracking Traders' Understanding of the Market Using e-Communication Data," PLOS ONE, Public Library of Science, vol. 6(10), pages 1-7, October.
    • Handle: RePEc:plo:pone00:0026705
    DOI: 10.1371/journal.pone.0026705
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0026705
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0026705&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0026705?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
    ---><---

    References listed on IDEAS

    as
    1. Diermeier, Daniel & Merlo, Antonio, 2000. "Government Turnover in Parliamentary Democracies," Journal of Economic Theory, Elsevier, vol. 94(1), pages 46-79, September.
    2. Roger Guimerà & Luís A. Nunes Amaral, 2005. "Functional cartography of complex metabolic networks," Nature, Nature, vol. 433(7028), pages 895-900, February.
    3. Eduardo G Altmann & Janet B Pierrehumbert & Adilson E Motter, 2009. "Beyond Word Frequency: Bursts, Lulls, and Scaling in the Temporal Distributions of Words," PLOS ONE, Public Library of Science, vol. 4(11), pages 1-7, November.
    4. Harrison Hong & Jeffrey D. Kubik & Jeremy C. Stein, 2005. "Thy Neighbor's Portfolio: Word‐of‐Mouth Effects in the Holdings and Trades of Money Managers," Journal of Finance, American Finance Association, vol. 60(6), pages 2801-2824, December.
    5. Jeremy Ginsberg & Matthew H. Mohebbi & Rajan S. Patel & Lynnette Brammer & Mark S. Smolinski & Larry Brilliant, 2009. "Detecting influenza epidemics using search engine query data," Nature, Nature, vol. 457(7232), pages 1012-1014, February.
    6. Serguei Saavedra & David Smith & Felix Reed-Tsochas, 2010. "Cooperation under Indirect Reciprocity and Imitative Trust," PLOS ONE, Public Library of Science, vol. 5(10), pages 1-6, October.
    7. Robert M. May & Simon A. Levin & George Sugihara, 2008. "Ecology for bankers," Nature, Nature, vol. 451(7181), pages 893-894, February.
    8. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
    9. Harris, Milton & Raviv, Artur, 1993. "Differences of Opinion Make a Horse Race," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 473-506.
    10. repec:bla:jfinan:v:59:y:2004:i:3:p:1259-1294 is not listed on IDEAS
    11. Duncan J. Watts, 2007. "A twenty-first century science," Nature, Nature, vol. 445(7127), pages 489-489, February.
    12. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    13. Marten Scheffer & Jordi Bascompte & William A. Brock & Victor Brovkin & Stephen R. Carpenter & Vasilis Dakos & Hermann Held & Egbert H. van Nes & Max Rietkerk & George Sugihara, 2009. "Early-warning signals for critical transitions," Nature, Nature, vol. 461(7260), pages 53-59, September.
    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. David Garcia & Frank Schweitzer, 2015. "Social signals and algorithmic trading of Bitcoin," Papers 1506.01513, arXiv.org, revised Sep 2015.
    2. Alberto Acerbi & Vasileios Lampos & Philip Garnett & R Alexander Bentley, 2013. "The Expression of Emotions in 20th Century Books," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-6, March.
    3. Niccolò Casnici & Pierpaolo Dondio & Roberto Casarin & Flaminio Squazzoni, 2015. "Decrypting Financial Markets through E-Joint Attention Efforts: On-Line Adaptive Networks of Investors in Periods of Market Uncertainty," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-15, August.
    4. Márton Mestyán & Taha Yasseri & János Kertész, 2013. "Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-8, August.
    5. Serguei Saavedra & Luis J. Gilarranz & Rudolf P. Rohr & Michael Schnabel & Brian Uzzi & Jordi Bascompte, 2014. "Stock fluctuations are correlated and amplified across networks of interlocking directorates," Papers 1410.6646, arXiv.org.
    6. Herm, Steffen & Callsen-Bracker, Hans-Markus & Kreis, Henning, 2014. "When the crowd evaluates soccer players’ market values: Accuracy and evaluation attributes of an online community," Sport Management Review, Elsevier, vol. 17(4), pages 484-492.
    7. Audrino, Francesco & Sigrist, Fabio & Ballinari, Daniele, 2020. "The impact of sentiment and attention measures on stock market volatility," International Journal of Forecasting, Elsevier, vol. 36(2), pages 334-357.

    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. Vishwesha Guttal & Srinivas Raghavendra & Nikunj Goel & Quentin Hoarau, 2016. "Lack of Critical Slowing Down Suggests that Financial Meltdowns Are Not Critical Transitions, yet Rising Variability Could Signal Systemic Risk," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-20, January.
    2. Ishani Chaudhuri & Parthajit Kayal, 2022. "Predicting Power of Ticker Search Volume in Indian Stock Market," Working Papers 2022-214, Madras School of Economics,Chennai,India.
    3. Karimi Rahjerdi, Bahareh & Ramamoorthy, Ramesh & Nazarimehr, Fahimeh & Rajagopal, Karthikeyan & Jafari, Sajad, 2022. "Indicating the synchronization bifurcation points using the early warning signals in two case studies: Continuous and explosive synchronization," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    4. Fushing, Hsieh & Jordà, Òscar & Beisner, Brianne & McCowan, Brenda, 2014. "Computing systemic risk using multiple behavioral and keystone networks: The emergence of a crisis in primate societies and banks," International Journal of Forecasting, Elsevier, vol. 30(3), pages 797-806.
    5. Martin Lindegren & Vasilis Dakos & Joachim P Gröger & Anna Gårdmark & Georgs Kornilovs & Saskia A Otto & Christian Möllmann, 2012. "Early Detection of Ecosystem Regime Shifts: A Multiple Method Evaluation for Management Application," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-9, July.
    6. Fantazzini, Dean, 2020. "Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 33-54.
    7. Zeng, Chunhua & Wang, Hua, 2012. "Noise and large time delay: Accelerated catastrophic regime shifts in ecosystems," Ecological Modelling, Elsevier, vol. 233(C), pages 52-58.
    8. Corsi, Fulvio & Lillo, Fabrizio & Pirino, Davide & Trapin, Luca, 2018. "Measuring the propagation of financial distress with Granger-causality tail risk networks," Journal of Financial Stability, Elsevier, vol. 38(C), pages 18-36.
    9. Cedric Mbanga & Ali F. Darrat & Jung Chul Park, 2019. "Investor sentiment and aggregate stock returns: the role of investor attention," Review of Quantitative Finance and Accounting, Springer, vol. 53(2), pages 397-428, August.
    10. Long Wen & Chang Liu & Haiyan Song, 2019. "Forecasting tourism demand using search query data: A hybrid modelling approach," Tourism Economics, , vol. 25(3), pages 309-329, May.
    11. Pedersen, Lasse Heje, 2022. "Game on: Social networks and markets," Journal of Financial Economics, Elsevier, vol. 146(3), pages 1097-1119.
    12. Marcus Alexander Ong, 2015. "An information theoretic analysis of stock returns, volatility and trading volumes," Applied Economics, Taylor & Francis Journals, vol. 47(36), pages 3891-3906, August.
    13. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    14. Timm O. Sprenger & Andranik Tumasjan & Philipp G. Sandner & Isabell M. Welpe, 2014. "Tweets and Trades: the Information Content of Stock Microblogs," European Financial Management, European Financial Management Association, vol. 20(5), pages 926-957, November.
    15. Qadan, Mahmoud, 2018. "Switches in price discovery: Are U.S. traders more qualified in making valuations?," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 221-234.
    16. Supachok Thakolsri & Yuthana Sethapramote & Komain Jiranyakul, 2016. "Implied Volatility Transmissions Between Thai and Selected Advanced Stock Markets," SAGE Open, , vol. 6(3), pages 21582440166, July.
    17. Sinha, Pankaj & Agnihotri, Shalini, 2014. "Investigating impact of volatility persistence, market asymmetry and information inflow on volatility of stock indices using bivariate GJR-GARCH," MPRA Paper 58303, University Library of Munich, Germany.
    18. Chuang, Wen-I & Liu, Hsiang-Hsi & Susmel, Rauli, 2012. "The bivariate GARCH approach to investigating the relation between stock returns, trading volume, and return volatility," Global Finance Journal, Elsevier, vol. 23(1), pages 1-15.
    19. Chaido Dritsaki, 2014. "The Dynamic Relationship between Stock Volatility and Trading Volume from the Athens Stock Exchange," International Journal of Empirical Finance, Research Academy of Social Sciences, vol. 3(3), pages 152-165.
    20. Pantzalis, Christos & Park, Jung Chul, 2014. "Too close for comfort? Geographic propinquity to political power and stock returns," Journal of Banking & Finance, Elsevier, vol. 48(C), pages 57-78.

    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:plo:pone00:0026705. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.