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Do investors herd in cryptocurrencies – and why?

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  • Kallinterakis, Vasileios
  • Wang, Ying

Abstract

We investigate herding and its possible determinants in the cryptocurrency market for the December 2013 – July 2018 period. Herding is significant (irrespective of Bitcoin’s presence and trends over time) and strongly asymmetric (appearing stronger during up-markets, low volatility and high volume days), with smaller cryptocurrencies enhancing its magnitude. Our findings suggest that the cryptocurrency market entails strong destabilizing potential, the latter being of particular relevance to the authorities entrusted with its regulatory treatment.

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  • Kallinterakis, Vasileios & Wang, Ying, 2019. "Do investors herd in cryptocurrencies – and why?," Research in International Business and Finance, Elsevier, vol. 50(C), pages 240-245.
    • Handle: RePEc:eee:riibaf:v:50:y:2019:i:c:p:240-245
    DOI: 10.1016/j.ribaf.2019.05.005
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    1. Symitsi, Efthymia & Chalvatzis, Konstantinos J., 2019. "The economic value of Bitcoin: A portfolio analysis of currencies, gold, oil and stocks," Research in International Business and Finance, Elsevier, vol. 48(C), pages 97-110.
    2. 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.
    3. Gkillas, Konstantinos & Katsiampa, Paraskevi, 2018. "An application of extreme value theory to cryptocurrencies," Economics Letters, Elsevier, vol. 164(C), pages 109-111.
    4. Charles P. Kindleberger & Robert Z. Aliber, 2005. "Manias, Panics and Crashes," Palgrave Macmillan Books, Palgrave Macmillan, edition 0, number 978-0-230-62804-5, December.
    5. Bouri, Elie & Gupta, Rangan & Roubaud, David, 2019. "Herding behaviour in cryptocurrencies," Finance Research Letters, Elsevier, vol. 29(C), pages 216-221.
    6. David Hirshleifer & Siew Hong Teoh, 2003. "Herd Behaviour and Cascading in Capital Markets: a Review and Synthesis," European Financial Management, European Financial Management Association, vol. 9(1), pages 25-66, March.
    7. Adrian (Wai-Kong) Cheung & Eduardo Roca & Jen-Je Su, 2015. "Crypto-currency bubbles: an application of the Phillips-Shi-Yu (2013) methodology on Mt. Gox bitcoin prices," Applied Economics, Taylor & Francis Journals, vol. 47(23), pages 2348-2358, May.
    8. Pieters, Gina & Vivanco, Sofia, 2017. "Financial regulations and price inconsistencies across Bitcoin markets," Information Economics and Policy, Elsevier, vol. 39(C), pages 1-14.
    9. Liao, Tsai-Ling & Huang, Chih-Jen & Wu, Chieh-Yuan, 2011. "Do fund managers herd to counter investor sentiment?," Journal of Business Research, Elsevier, vol. 64(2), pages 207-212, February.
    10. Choi, Nicole & Sias, Richard W., 2009. "Institutional industry herding," Journal of Financial Economics, Elsevier, vol. 94(3), pages 469-491, December.
    11. Urquhart, Andrew, 2018. "What causes the attention of Bitcoin?," Economics Letters, Elsevier, vol. 166(C), pages 40-44.
    12. Fry, John & Cheah, Eng-Tuck, 2016. "Negative bubbles and shocks in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 343-352.
    13. Arjoon, Vaalmikki & Bhatnagar, Chandra Shekhar, 2017. "Dynamic herding analysis in a frontier market," Research in International Business and Finance, Elsevier, vol. 42(C), pages 496-508.
    14. Hao Jiang & Michela Verardo, 2018. "Does Herding Behavior Reveal Skill? An Analysis of Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 73(5), pages 2229-2269, October.
    15. Blau, Benjamin M., 2018. "Price dynamics and speculative trading in Bitcoin," Research in International Business and Finance, Elsevier, vol. 43(C), pages 15-21.
    16. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-896, July.
    17. Jiang, Hao & Verardo, Michela, 2018. "Does herding behavior reveal skill? An analysis of mutual fund performance," LSE Research Online Documents on Economics 86372, London School of Economics and Political Science, LSE Library.
    18. Celiker, Umut & Chowdhury, Jaideep & Sonaer, Gokhan, 2015. "Do mutual funds herd in industries?," Journal of Banking & Finance, Elsevier, vol. 52(C), pages 1-16.
    19. Vidal-Tomás, David & Ibáñez, Ana M. & Farinós, José E., 2019. "Herding in the cryptocurrency market: CSSD and CSAD approaches," Finance Research Letters, Elsevier, vol. 30(C), pages 181-186.
    20. Natividad Blasco & Pilar Corredor & Sandra Ferreruela, 2012. "Does herding affect volatility? Implications for the Spanish stock market," Quantitative Finance, Taylor & Francis Journals, vol. 12(2), pages 311-327, July.
    21. Spyros Spyrou, 2013. "Herding in financial markets: a review of the literature," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 5(2), pages 175-194, November.
    22. Devenow, Andrea & Welch, Ivo, 1996. "Rational herding in financial economics," European Economic Review, Elsevier, vol. 40(3-5), pages 603-615, April.
    23. Cheah, Eng-Tuck & Fry, John, 2015. "Speculative bubbles in Bitcoin markets? An empirical investigation into the fundamental value of Bitcoin," Economics Letters, Elsevier, vol. 130(C), pages 32-36.
    24. Economou, Fotini & Gavriilidis, Konstantinos & Goyal, Abhinav & Kallinterakis, Vasileios, 2015. "Herding dynamics in exchange groups: Evidence from Euronext," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 34(C), pages 228-244.
    25. Blake, David & Sarno, Lucio & Zinna, Gabriele, 2017. "The market for lemmings: The herding behavior of pension funds," Journal of Financial Markets, Elsevier, vol. 36(C), pages 17-39.
    26. Phillip, Andrew & Chan, Jennifer S.K. & Peiris, Shelton, 2018. "A new look at Cryptocurrencies," Economics Letters, Elsevier, vol. 163(C), pages 6-9.
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    Cited by:

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    4. Mohamad, Azhar & Stavroyiannis, Stavros, 2022. "Do birds of a feather flock together? Evidence from time-varying herding behaviour of bitcoin and foreign exchange majors during Covid-19," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    5. Kyriazis, Nikolaos & Papadamou, Stephanos & Corbet, Shaen, 2020. "A systematic review of the bubble dynamics of cryptocurrency prices," Research in International Business and Finance, Elsevier, vol. 54(C).
    6. Mercik, Aleksander & Słoński, Tomasz & Karaś, Marta, 2024. "Understanding crypto-asset exposure: An investigation of its impact on performance and stock sensitivity among listed companies," International Review of Financial Analysis, Elsevier, vol. 92(C).
    7. Liu, Jian & Julaiti, Jiansuer & Gou, Shangde, 2024. "Decomposing interconnectedness: A study of cryptocurrency spillover effects in global financial markets," Finance Research Letters, Elsevier, vol. 61(C).
    8. Yarovaya, Larisa & Matkovskyy, Roman & Jalan, Akanksha, 2021. "The effects of a “black swan” event (COVID-19) on herding behavior in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    9. Jia, Boxiang & Shen, Dehua & Zhang, Wei, 2022. "Extreme sentiment and herding: Evidence from the cryptocurrency market," Research in International Business and Finance, Elsevier, vol. 63(C).
    10. Ben Osman, Myriam & Galariotis, Emilios & Guesmi, Khaled & Hamdi, Haykel & Naoui, Kamel, 2024. "Are markets sentiment driving the price bubbles in the virtual?," International Review of Economics & Finance, Elsevier, vol. 89(PB), pages 272-285.
    11. Imran Yousaf & Shoaib Ali & Elie Bouri & Anupam Dutta, 2021. "Herding on Fundamental/Nonfundamental Information During the COVID-19 Outbreak and Cyber-Attacks: Evidence From the Cryptocurrency Market," SAGE Open, , vol. 11(3), pages 21582440211, July.
    12. Bennett, Donyetta & Mekelburg, Erik & Williams, T.H., 2023. "BeFi meets DeFi: A behavioral finance approach to decentralized finance asset pricing," Research in International Business and Finance, Elsevier, vol. 65(C).
    13. Zhao, Yuan & Liu, Nan & Li, Wanpeng, 2022. "Industry herding in crypto assets," International Review of Financial Analysis, Elsevier, vol. 84(C).
    14. Andrikopoulos, Panagiotis & Gebka, Bartosz & Kallinterakis, Vasileios, 2021. "Regulatory mood-congruence and herding: Evidence from cannabis stocks," Journal of Economic Behavior & Organization, Elsevier, vol. 185(C), pages 842-864.
    15. Ren, Boru & Lucey, Brian, 2023. "Herding in the Chinese renewable energy market: Evidence from a bootstrapping time-varying coefficient autoregressive model," Energy Economics, Elsevier, vol. 119(C).
    16. Park, Beum-Jo, 2022. "The COVID-19 pandemic, volatility, and trading behavior in the bitcoin futures market," Research in International Business and Finance, Elsevier, vol. 59(C).
    17. Ozkan Haykir & Ibrahim Yagli, 2022. "Speculative bubbles and herding in cryptocurrencies," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-33, December.
    18. Shi, Guiqiang & Shen, Dehua & Zhu, Zhaobo, 2024. "Herding towards carbon neutrality: The role of investor attention," International Review of Financial Analysis, Elsevier, vol. 91(C).
    19. Papadamou, Stephanos & Kyriazis, Nikolaos A. & Tzeremes, Panayiotis & Corbet, Shaen, 2021. "Herding behaviour and price convergence clubs in cryptocurrencies during bull and bear markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
    20. Almeida, José & Gonçalves, Tiago Cruz, 2023. "A systematic literature review of investor behavior in the cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    21. Ren, Boru & Lucey, Brian, 2022. "Do clean and dirty cryptocurrency markets herd differently?," Finance Research Letters, Elsevier, vol. 47(PB).
    22. David Vidal-Tomás & Ana M. Ibáñez & José E. Farinós, 2021. "The Effect of the Launch of Bitcoin Futures on the Cryptocurrency Market: An Economic Efficiency Approach," Mathematics, MDPI, vol. 9(4), pages 1-14, February.
    23. Scharnowski, Stefan & Shi, Yanghua, 2024. "Intraday herding and attention around the clock," Journal of Behavioral and Experimental Finance, Elsevier, vol. 41(C).

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    More about this item

    Keywords

    Herding; Cryptocurrencies; Bitcoin;
    All these keywords.

    JEL classification:

    • G40 - Financial Economics - - Behavioral Finance - - - General
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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