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Herding behavior in exploring the predictability of price clustering in cryptocurrency market

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  • Hachicha, Fatma
  • Masmoudi, Afif
  • Abid, Ilyes
  • Obeid, Hassan

Abstract

We propose the K-means approach and the Hidden Markov Model (HMM), to predict the phenomenon of price clustering of the cryptocurrency market. This approach aims to understand the relationship of price clustering with herding behavior, volatility, price, and economic policy uncertainty (EPU). Our results indicate that the (HMM) with four states has the best one-step-ahead forecasting performance. The results gave new insights into the financial analysis of cryptocurrency market about the dynamic relationship between price clustering regimes and different states of the explanatory variable. Our finding proves the efficiency of (HMM) for our sample and provides a good predictability.

Suggested Citation

  • Hachicha, Fatma & Masmoudi, Afif & Abid, Ilyes & Obeid, Hassan, 2023. "Herding behavior in exploring the predictability of price clustering in cryptocurrency market," Finance Research Letters, Elsevier, vol. 57(C).
    • Handle: RePEc:eee:finlet:v:57:y:2023:i:c:s1544612323005500
    DOI: 10.1016/j.frl.2023.104178
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    1. David L. Ikenberry & James P. Weston, 2008. "Clustering in US Stock Prices after Decimalisation," European Financial Management, European Financial Management Association, vol. 14(1), pages 30-54, January.
    2. Yousaf, Imran & Yarovaya, Larisa, 2022. "Static and dynamic connectedness between NFTs, Defi and other assets: Portfolio implication," Global Finance Journal, Elsevier, vol. 53(C).
    3. Christian Hotz‐Behofsits & Florian Huber & Thomas Otto Zörner, 2018. "Predicting crypto‐currencies using sparse non‐Gaussian state space models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(6), pages 627-640, September.
    4. 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.
    5. Aalborg, Halvor Aarhus & Molnár, Peter & de Vries, Jon Erik, 2019. "What can explain the price, volatility and trading volume of Bitcoin?," Finance Research Letters, Elsevier, vol. 29(C), pages 255-265.
    6. Hu, Bill & McInish, Thomas & Miller, Jonathan & Zeng, Li, 2019. "Intraday price behavior of cryptocurrencies," Finance Research Letters, Elsevier, vol. 28(C), pages 337-342.
    7. Catania, Leopoldo & Grassi, Stefano & Ravazzolo, Francesco, 2019. "Forecasting cryptocurrencies under model and parameter instability," International Journal of Forecasting, Elsevier, vol. 35(2), pages 485-501.
    8. Urquhart, Andrew, 2017. "Price clustering in Bitcoin," Economics Letters, Elsevier, vol. 159(C), pages 145-148.
    9. Blau, Benjamin M. & Griffith, Todd G., 2016. "Price clustering and the stability of stock prices," Journal of Business Research, Elsevier, vol. 69(10), pages 3933-3942.
    10. Robert I. Webb & Jason Mitchell, 2001. "Clustering and psychological barriers: the importance of numbers," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 21(5), pages 395-428, May.
    11. Demir, Ender & Gozgor, Giray & Lau, Chi Keung Marco & Vigne, Samuel A., 2018. "Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation," Finance Research Letters, Elsevier, vol. 26(C), pages 145-149.
    12. A. Hachicha & F. Hachicha, 2021. "Analysis of the bitcoin stock market indexes using comparative study of two models SV with MCMC algorithm," Review of Quantitative Finance and Accounting, Springer, vol. 56(2), pages 647-673, February.
    13. Yang, Wan-Ru & Chuang, Ming-Che, 2023. "Do investors herd in a volatile market? Evidence of dynamic herding in Taiwan, China, and US stock markets," Finance Research Letters, Elsevier, vol. 52(C).
    14. Galariotis, Emilios C. & Rong, Wu & Spyrou, Spyros I., 2015. "Herding on fundamental information: A comparative study," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 589-598.
    15. Yao, Juan & Ma, Chuanchan & He, William Peng, 2014. "Investor herding behaviour of Chinese stock market," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 12-29.
    16. Yen, Kuang-Chieh & Cheng, Hui-Pei, 2021. "Economic policy uncertainty and cryptocurrency volatility," Finance Research Letters, Elsevier, vol. 38(C).
    17. Bleher, Johannes & Dimpfl, Thomas, 2019. "Today I got a million, tomorrow, I don't know: On the predictability of cryptocurrencies by means of Google search volume," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 147-159.
    18. Lucey, Brian M. & Vigne, Samuel A. & Yarovaya, Larisa & Wang, Yizhi, 2022. "The cryptocurrency uncertainty index," Finance Research Letters, Elsevier, vol. 45(C).
    19. Blau, Benjamin M., 2018. "Price dynamics and speculative trading in Bitcoin," Research in International Business and Finance, Elsevier, vol. 43(C), pages 15-21.
    20. 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).
    21. Tan, Lin & Chiang, Thomas C. & Mason, Joseph R. & Nelling, Edward, 2008. "Herding behavior in Chinese stock markets: An examination of A and B shares," Pacific-Basin Finance Journal, Elsevier, vol. 16(1-2), pages 61-77, January.
    22. Ballis, Antonis & Drakos, Konstantinos, 2020. "Testing for herding in the cryptocurrency market," Finance Research Letters, Elsevier, vol. 33(C).
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