IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v29y2019icp379-383.html
   My bibliography  Save this article

Is anti-herding behavior spurious?

Author

Listed:
  • Stavroyiannis, Stavros
  • Babalos, Vassilios
  • Bekiros, Stelios
  • Lahmiri, Salim

Abstract

Herding behavior has been in the epicenter of a heated debate over the past three decades across traditional and alternative asset markets. Establishing the existence of herding relies on a standard regression-based testing procedure. Employing Monte Carlo simulations we show that spurious anti-herding behavior might emerge even if the series are random and totally uncorrelated, provided that the residuals of the model fail to conform to some of the assumptions of standard linear regression. The simulations from a t-student distribution are examined as a function of the degrees of freedom, the length of the simulations, and the number of series.

Suggested Citation

  • Stavroyiannis, Stavros & Babalos, Vassilios & Bekiros, Stelios & Lahmiri, Salim, 2019. "Is anti-herding behavior spurious?," Finance Research Letters, Elsevier, vol. 29(C), pages 379-383.
    • Handle: RePEc:eee:finlet:v:29:y:2019:i:c:p:379-383
    DOI: 10.1016/j.frl.2018.09.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612318304525
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2018.09.003?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. Chang, Eric C. & Cheng, Joseph W. & Khorana, Ajay, 2000. "An examination of herd behavior in equity markets: An international perspective," Journal of Banking & Finance, Elsevier, vol. 24(10), pages 1651-1679, October.
    2. Chiang, Thomas C. & Zheng, Dazhi, 2010. "An empirical analysis of herd behavior in global stock markets," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1911-1921, August.
    3. Chiang, Thomas C. & Li, Jiandong & Tan, Lin, 2010. "Empirical investigation of herding behavior in Chinese stock markets: Evidence from quantile regression analysis," Global Finance Journal, Elsevier, vol. 21(1), pages 111-124.
    4. Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2013. "Forecasting metal prices: Do forecasters herd?," Journal of Banking & Finance, Elsevier, vol. 37(1), pages 150-158.
    5. Bohl, Martin T. & Branger, Nicole & Trede, Mark, 2017. "The case for herding is stronger than you think," Journal of Banking & Finance, Elsevier, vol. 85(C), pages 30-40.
    6. Stavros Stavroyiannis & Vassilios Babalos, 2017. "Herding, Faith-Based Investments and the Global Financial Crisis: Empirical Evidence From Static and Dynamic Models," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 18(4), pages 478-489, October.
    7. Vassilios Babalos & Stavros Stavroyiannis, 2015. "Herding, anti-herding behaviour in metal commodities futures: a novel portfolio-based approach," Applied Economics, Taylor & Francis Journals, vol. 47(46), pages 4952-4966, October.
    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. Scharnowski, Stefan & Shi, Yanghua, 2024. "Intraday herding and attention around the clock," Journal of Behavioral and Experimental Finance, Elsevier, vol. 41(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. Stavroyiannis, Stavros & Babalos, Vassilios, 2019. "Herding behavior in cryptocurrencies revisited: Novel evidence from a TVP model," Journal of Behavioral and Experimental Finance, Elsevier, vol. 22(C), pages 57-63.
    2. Babalos, Vassilios & Stavroyiannis, Stavros & Gupta, Rangan, 2015. "Do commodity investors herd? Evidence from a time-varying stochastic volatility model," Resources Policy, Elsevier, vol. 46(P2), pages 281-287.
    3. Puput Tri Komalasari & Marwan Asri & Bernardinus M. Purwanto & Bowo Setiyono, 2022. "Herding behaviour in the capital market: What do we know and what is next?," Management Review Quarterly, Springer, vol. 72(3), pages 745-787, September.
    4. Humayun Kabir, M. & Shakur, Shamim, 2018. "Regime-dependent herding behavior in Asian and Latin American stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 47(C), pages 60-78.
    5. Xolani Sibande & Rangan Gupta & Riza Demirer & Elie Bouri, 2023. "Investor Sentiment and (Anti) Herding in the Currency Market: Evidence from Twitter Feed Data," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 24(1), pages 56-72, January.
    6. Zhenxi Chen & Jing Ru, 2021. "Herding and capitalization size in the Chinese stock market: a micro-foundation evidence," Empirical Economics, Springer, vol. 60(4), pages 1895-1911, April.
    7. Zhao, Yuan & Liu, Nan & Li, Wanpeng, 2022. "Industry herding in crypto assets," International Review of Financial Analysis, Elsevier, vol. 84(C).
    8. Rubesam, Alexandre & Raimundo, Gerson de Souza, 2022. "Covid-19 and herding in global equity markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 35(C).
    9. Coskun, Esra Alp & Lau, Chi Keung Marco & Kahyaoglu, Hakan, 2020. "Uncertainty and herding behavior: evidence from cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 54(C).
    10. Vijay Kumar Shrotryia & Himanshi Kalra, 2021. "Analysis of Sectoral Herding through Quantile Regression: A Study of S&P BSE 500 Stocks," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 20(1), pages 1-16, June.
    11. Júlio Lobão, 2022. "Herding Behavior in the Market for Green Cryptocurrencies: Evidence from CSSD and CSAD Approaches," Sustainability, MDPI, vol. 14(19), pages 1-17, October.
    12. Aytaç, Beysül & Coqueret, Guillaume & Mandou, Cyrille, 2018. "Herding behavior among wine investors," Economic Modelling, Elsevier, vol. 68(C), pages 318-328.
    13. Kumar, Ashish & Badhani, K.N. & Bouri, Elie & Saeed, Tareq, 2021. "Herding behavior in the commodity markets of the Asia-Pacific region," Finance Research Letters, Elsevier, vol. 41(C).
    14. Bohl, Martin T. & Branger, Nicole & Trede, Mark, 2017. "The case for herding is stronger than you think," Journal of Banking & Finance, Elsevier, vol. 85(C), pages 30-40.
    15. Syed Faisal Hasssan Bukhari & Waqar Yasir & Christian Espinosa Méndez & Zia Mustafa, 2023. "Sectoral Comparison of Herding During Global Financial Crisis and Covid-19: Comparative Analysis of Shariah Compliant and Conventional Stocks," Journal of Economic Impact, Science Impact Publishers, vol. 5(3), pages 202-210.
    16. Gębka, Bartosz & Wohar, Mark E., 2013. "International herding: Does it differ across sectors?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 23(C), pages 55-84.
    17. Kaiser, Lars & Stöckl, Sebastian, 2020. "Cryptocurrencies: Herding and the transfer currency," Finance Research Letters, Elsevier, vol. 33(C).
    18. Charilaos Mertzanis & Noha Allam, 2018. "Political Instability and Herding Behaviour: Evidence from Egypt’s Stock Market," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(1), pages 29-59, April.
    19. Syed Riaz Mahmood Ali, 2022. "Herding in different states and terms: evidence from the cryptocurrency market," Journal of Asset Management, Palgrave Macmillan, vol. 23(4), pages 322-336, July.
    20. Galariotis, Emilios C. & Krokida, Styliani-Iris & Spyrou, Spyros I., 2016. "Bond market investor herding: Evidence from the European financial crisis," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 367-375.

    More about this item

    Keywords

    Spurious anti-herding; Multivariate Monte Carlo; Statistical significance;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    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:eee:finlet:v:29:y:2019:i:c:p:379-383. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    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.