IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v4y2018i1d10.1057_s41599-018-0145-1.html
   My bibliography  Save this article

Long-term ecology of investors in a financial market

Author

Listed:
  • Federico Musciotto

    (Università di Palermo)

  • Luca Marotta

    (Università di Palermo)

  • Jyrki Piilo

    (University of Turku)

  • Rosario N. Mantegna

    (Università di Palermo
    Complexity Science Hub Vienna
    University College London)

Abstract

The cornerstone of modern finance is the efficient market hypothesis. Under this hypothesis all information available about a financial asset is immediately incorporated into its price dynamics by fully rational investors. In contrast to this hypothesis many studies have pointed out behavioral biases in investors. Recently it has become possible to access databases that track the trading decisions of investors. Studies of such databases have shown that investors acting in a financial market are highly heterogeneous among them, and that heterogeneity is a common characteristic of many financial markets. The article describes an empirical study of the daily trading decisions of all Finnish investors investing Nokia stock over a time period of 15 years. The investigation is performed by adapting and using methods and tools in network science. By investigating daily trading decisions, and by constructing the time-evolution of statistically validated networks of investors, clusters of investors—and their time evolution— which are characterized by similar trading profiles are detected. These clusters are performing distinct trading decisions on time scales ranging from several months to twelve years. These empirical observations show the presence of an ecology of groups of investors characterized by different attributes and by various investment styles over many years. Some of the detected clusters present a persistent over-expression of specific investor categories. The study shows that the logarithm of the ratio of pairs of statistically validated trading decisions is different for different values of the market volatility. These findings suggest that an ecology of investors is present in financial markets and that groups of traders are always competing, adopting, using and eventually discarding new investment strategies. This adaptation process is observed over a multiplicity of time scales, and is compatible with several conclusions of behavioral finance and with the assumptions of the so-called adaptive market hypothesis.

Suggested Citation

  • Federico Musciotto & Luca Marotta & Jyrki Piilo & Rosario N. Mantegna, 2018. "Long-term ecology of investors in a financial market," Palgrave Communications, Palgrave Macmillan, vol. 4(1), pages 1-12, December.
    • Handle: RePEc:pal:palcom:v:4:y:2018:i:1:d:10.1057_s41599-018-0145-1
    DOI: 10.1057/s41599-018-0145-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-018-0145-1
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/s41599-018-0145-1?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. Fabrizio Lillo & Salvatore Miccich� & Michele Tumminello & Jyrki Piilo & Rosario N. Mantegna, 2015. "How news affects the trading behaviour of different categories of investors in a financial market," Quantitative Finance, Taylor & Francis Journals, vol. 15(2), pages 213-229, February.
    2. Daniel Dorn & Gur Huberman, 2005. "Talk and Action: What Individual Investors Say and What They Do," Review of Finance, Springer, vol. 9(4), pages 437-481, December.
    3. Gervais, Simon & Odean, Terrance, 2001. "Learning to be Overconfident," The Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 1-27.
    4. Lakonishok, Josef & Shleifer, Andrei & Vishny, Robert W., 1992. "The impact of institutional trading on stock prices," Journal of Financial Economics, Elsevier, vol. 32(1), pages 23-43, August.
    5. Laurent E. Calvet & John Y. Campbell & Paolo Sodini, 2007. "Down or Out: Assessing the Welfare Costs of Household Investment Mistakes," Journal of Political Economy, University of Chicago Press, vol. 115(5), pages 707-747, October.
    6. J. Doyne Farmer, 2002. "Market force, ecology and evolution," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 11(5), pages 895-953, November.
    7. Daniel Dorn & Gur Huberman & Paul Sengmueller, 2008. "Correlated Trading and Returns," Journal of Finance, American Finance Association, vol. 63(2), pages 885-920, April.
    8. Fei Ren & Wei-Xing Zhou, 2013. "Analysis of trade packages in the Chinese stock market," Quantitative Finance, Taylor & Francis Journals, vol. 13(7), pages 1071-1089, January.
    9. Jean-Philippe Bouchaud & J. Doyne Farmer & Fabrizio Lillo, 2008. "How markets slowly digest changes in supply and demand," Papers 0809.0822, arXiv.org.
    10. Lei Feng & Mark Seasholes, 2005. "Do Investor Sophistication and Trading Experience Eliminate Behavioral Biases in Financial Markets?," Review of Finance, Springer, vol. 9(3), pages 305-351, September.
    11. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    12. Ludvig Bohlin & Martin Rosvall, 2014. "Stock portfolio structure of individual investors infers future trading behavior," Papers 1402.2494, arXiv.org, revised Aug 2014.
    13. William N. Goetzmann & Alok Kumar, 2008. "Equity Portfolio Diversification," Review of Finance, European Finance Association, vol. 12(3), pages 433-463.
    14. David Morton de Lachapelle & Damien Challet, 2009. "Turnover, account value and diversification of real traders: evidence of collective portfolio optimizing behavior," Papers 0912.4723, arXiv.org, revised Jun 2010.
    15. John R. Graham & Campbell R. Harvey & Hai Huang, 2009. "Investor Competence, Trading Frequency, and Home Bias," Management Science, INFORMS, vol. 55(7), pages 1094-1106, July.
    16. Robert J. Shiller, 2003. "From Efficient Markets Theory to Behavioral Finance," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 83-104, Winter.
    17. Thomas Lux & Michele Marchesi, 1999. "Scaling and criticality in a stochastic multi-agent model of a financial market," Nature, Nature, vol. 397(6719), pages 498-500, February.
    18. Markus Glaser & Martin Weber, 2007. "Overconfidence and trading volume," The Geneva Papers on Risk and Insurance Theory, Springer;International Association for the Study of Insurance Economics (The Geneva Association), vol. 32(1), pages 1-36, June.
    19. repec:bla:jfinan:v:53:y:1998:i:5:p:1775-1798 is not listed on IDEAS
    20. Andrei Kirilenko & Albert S. Kyle & Mehrdad Samadi & Tugkan Tuzun, 2017. "The Flash Crash: High-Frequency Trading in an Electronic Market," Journal of Finance, American Finance Association, vol. 72(3), pages 967-998, June.
    21. Lei Feng & Mark S. Seasholes, 2005. "Do Investor Sophistication and Trading Experience Eliminate Behavioral Biases in Financial Markets?," Review of Finance, European Finance Association, vol. 9(3), pages 305-351.
    22. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    23. Lakonishok, Josef & Maberly, Edwin, 1990. "The Weekend Effect: Trading Patterns of Individual and Institutional Investors," Journal of Finance, American Finance Association, vol. 45(1), pages 231-243, March.
    24. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    25. Ludvig Bohlin & Martin Rosvall, 2014. "Stock Portfolio Structure of Individual Investors Infers Future Trading Behavior," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-8, July.
    26. Alan Kirman, 1993. "Ants, Rationality, and Recruitment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(1), pages 137-156.
    27. Mark Grinblatt & Matti Keloharju, 2009. "Sensation Seeking, Overconfidence, and Trading Activity," Journal of Finance, American Finance Association, vol. 64(2), pages 549-578, April.
    28. Mark Grinblatt & Matti Keloharju, 2001. "How Distance, Language, and Culture Influence Stockholdings and Trades," Journal of Finance, American Finance Association, vol. 56(3), pages 1053-1073, June.
    29. John R. Nofsinger & Richard W. Sias, 1999. "Herding and Feedback Trading by Institutional and Individual Investors," Journal of Finance, American Finance Association, vol. 54(6), pages 2263-2295, December.
    30. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    31. 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.
    32. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    33. Terrance Odean, 1999. "Do Investors Trade Too Much?," American Economic Review, American Economic Association, vol. 89(5), pages 1279-1298, December.
    34. Grinblatt, Mark & Keloharju, Matti, 2000. "The investment behavior and performance of various investor types: a study of Finland's unique data set," Journal of Financial Economics, Elsevier, vol. 55(1), pages 43-67, January.
    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. Aymeric Vie & J. Doyne Farmer, 2023. "Towards Evology: a Market Ecology Agent-Based Model of US Equity Mutual Funds II," Papers 2302.01216, arXiv.org.
    2. Pankaj Kumar, 2021. "Deep Hawkes Process for High-Frequency Market Making," Papers 2109.15110, arXiv.org.
    3. Baptiste Barreau & Laurent Carlier & Damien Challet, 2019. "Deep Prediction of Investor Interest: a Supervised Clustering Approach," Papers 1909.05289, arXiv.org, revised Feb 2021.
    4. Syed Qasim Shah & Izlin Ismail & Aidial Rizal bin Shahrin, 2020. "Heterogeneous investors and deterioration of market integrity: an analysis of market manipulation cases," Journal of Financial Crime, Emerald Group Publishing Limited, vol. 30(2), pages 389-403, May.
    5. Chen, Zhang-HangJian & Wu, Wang-Long & Li, Sai-Ping & Bao, Kun & Koedijk, Kees G., 2024. "Social media information diffusion and excess stock returns co-movement," International Review of Financial Analysis, Elsevier, vol. 91(C).
    6. Geetika Madaan & Sanjeet Singh, 2019. "An Analysis of Behavioral Biases in Investment Decision-Making," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 10(4), pages 55-67, July.
    7. Takumi Sueshige & Didier Sornette & Hideki Takayasu & Misako Takayasu, 2019. "Classification of position management strategies at the order-book level and their influences on future market-price formation," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-19, August.
    8. Carlo Campajola & Fabrizio Lillo & Daniele Tantari, 2019. "Unveiling the relation between herding and liquidity with trader lead-lag networks," Papers 1909.10807, arXiv.org, revised Mar 2020.
    9. Matthew Oldham, 2019. "Understanding How Short-Termism and a Dynamic Investor Network Affects Investor Returns: An Agent-Based Perspective," Complexity, Hindawi, vol. 2019, pages 1-21, July.
    10. Maarten P. Scholl & Anisoara Calinescu & J. Doyne Farmer, 2021. "How market ecology explains market malfunction," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 118(26), pages 2015574118-, June.
    11. Marcus Cordi & Serge Kassibrakis & Damien Challet, 2018. "The market nanostructure origin of asset price time reversal asymmetry," Working Papers hal-01966419, HAL.
    12. Kun Xing & Honggang Li, 2024. "Market Ecology: Trading Strategies and Market Volatility," Computational Economics, Springer;Society for Computational Economics, vol. 64(6), pages 3333-3351, December.
    13. Marcus Cordi & Damien Challet & Serge Kassibrakis, 2021. "The market nanostructure origin of asset price time reversal asymmetry," Quantitative Finance, Taylor & Francis Journals, vol. 21(2), pages 295-304, February.
    14. Zain UI Abideen & Zeeshan Ahmed & Huan Qiu & Yiwei Zhao, 2023. "Do Behavioral Biases Affect Investors’ Investment Decision Making? Evidence from the Pakistani Equity Market," Risks, MDPI, vol. 11(6), pages 1-32, June.
    15. Baptiste Barreau & Laurent Carlier & Damien Challet, 2019. "Deep Prediction of Investor Interest: a Supervised Clustering Approach," Papers 1909.05289, arXiv.org, revised Feb 2021.
    16. Semenova, Valentina & Winkler, Julian, 2020. "Reddit's Self-Organised Bull Runs," MPRA Paper 105443, University Library of Munich, Germany.
    17. Margarita Baltakienė & Kęstutis Baltakys & Juho Kanniainen & Dino Pedreschi & Fabrizio Lillo, 2019. "Clusters of investors around initial public offering," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-14, December.
    18. Wojciech Wisniewski & Yuri Kalnishkan & David Lindsay & Si^an Lindsay, 2024. "Temporal distribution of clusters of investors and their application in prediction with expert advice," Papers 2406.19403, arXiv.org.
    19. Takumi Sueshige & Kiyoshi Kanazawa & Hideki Takayasu & Misako Takayasu, 2018. "Ecology of trading strategies in a forex market for limit and market orders," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-14, December.
    20. Oldham, Matthew, 2020. "Quantifying the concerns of Dimon and Buffett with data and computation," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).

    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. Barber, Brad M. & Odean, Terrance, 2013. "The Behavior of Individual Investors," 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 1533-1570, Elsevier.
    2. Musciotto, Federico & Marotta, Luca & Miccichè, Salvatore & Piilo, Jyrki & Mantegna, Rosario N., 2016. "Patterns of trading profiles at the Nordic Stock Exchange. A correlation-based approach," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 267-278.
    3. Fotini Economou & Konstantinos Gavriilidis & Bartosz Gebka & Vasileios Kallinterakis, 2022. "Feedback trading: a review of theory and empirical evidence," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 15(4), pages 429-476, February.
    4. Liu, Hongqi & Peng, Cameron & Xiong, Wei A. & Xiong, Wei, 2022. "Taming the bias zoo," Journal of Financial Economics, Elsevier, vol. 143(2), pages 716-741.
    5. Liu, Hongqi & Peng, Cameron & Wei, Xiong & Wei, Xiong, 2022. "Taming the bias zoo," LSE Research Online Documents on Economics 109301, London School of Economics and Political Science, LSE Library.
    6. Lu, Xiaomeng & Zhang, Yong & Zhang, Yixing & Wang, Lin, 2020. "Can investment advisors promote rational investment? Evidence from micro-data in China," Economic Modelling, Elsevier, vol. 86(C), pages 251-263.
    7. Maximilian Koestner & Benjamin Loos & Steffen Meyer & Andreas Hackethal, 2017. "Do individual investors learn from their mistakes?," Journal of Business Economics, Springer, vol. 87(5), pages 669-703, July.
    8. Itzhak Venezia, 2018. "Lecture Notes in Behavioral Finance," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 10751, August.
    9. Talpsepp, Tõnn & Liivamägi, Kristjan & Vaarmets, Tarvo, 2020. "Academic abilities, education and performance in the stock market," Journal of Banking & Finance, Elsevier, vol. 117(C).
    10. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, September.
    11. Markus Glaser & Thomas Langer & Martin Weber, 2007. "On the Trend Recognition and Forecasting Ability of Professional Traders," Decision Analysis, INFORMS, vol. 4(4), pages 176-193, December.
    12. Michele Tumminello & Fabrizio Lillo & Jyrki Piilo & Rosario N. Mantegna, 2011. "Identification of clusters of investors from their real trading activity in a financial market," Papers 1107.3942, arXiv.org.
    13. Daniel, Kent & Hirshleifer, David & Teoh, Siew Hong, 2002. "Investor psychology in capital markets: evidence and policy implications," Journal of Monetary Economics, Elsevier, vol. 49(1), pages 139-209, January.
    14. Glaser, Markus & Weber, Martin, 2009. "Which past returns affect trading volume?," Journal of Financial Markets, Elsevier, vol. 12(1), pages 1-31, February.
    15. Merkle, Christoph, 2017. "Financial overconfidence over time: Foresight, hindsight, and insight of investors," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 68-87.
    16. David Hirshleifer, 2001. "Investor Psychology and Asset Pricing," Journal of Finance, American Finance Association, vol. 56(4), pages 1533-1597, August.
    17. Magron, Camille & Merli, Maxime, 2015. "Repurchase behavior of individual investors, sophistication and regret," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 15-26.
    18. Didier SORNETTE, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based Models," Swiss Finance Institute Research Paper Series 14-25, Swiss Finance Institute.
    19. Forman, John & Horton, Joanne, 2019. "Overconfidence, position size, and the link to performance," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 291-309.
    20. Richards, Daniel W. & Willows, Gizelle D., 2018. "Who trades profusely? The characteristics of individual investors who trade frequently," Global Finance Journal, Elsevier, vol. 35(C), pages 1-11.

    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:pal:palcom:v:4:y:2018:i:1:d:10.1057_s41599-018-0145-1. 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: https://www.nature.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.