IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v59y2024ics1544612323011352.html
   My bibliography  Save this article

A U-shaped relationship between the crypto fear-greed index and the price synchronicity of cryptocurrencies

Author

Listed:
  • Wang, Jying-Nan
  • Liu, Hung-Chun
  • Hsu, Yuan-Teng

Abstract

In this study, we use intraday data on Bitcoin, Ethereum, Litcoin, and Monero, traded on the Bitfinex exchange, to investigate the impact of the crypto fear and greed index (FGI) on the pairwise price synchronicity of these cryptocurrencies. Based on data from February 2018 to June 2023, our results show that the relationship between investors’ collective sentiment (the FGI) and price synchronicity (as measured by the realized correlation) exhibits a U-shaped pattern rather than a linear one. This is the first study to document a U-shaped relationship between FGI-based online investor sentiment and the price synchronicity of cryptocurrencies.

Suggested Citation

  • Wang, Jying-Nan & Liu, Hung-Chun & Hsu, Yuan-Teng, 2024. "A U-shaped relationship between the crypto fear-greed index and the price synchronicity of cryptocurrencies," Finance Research Letters, Elsevier, vol. 59(C).
    • Handle: RePEc:eee:finlet:v:59:y:2024:i:c:s1544612323011352
    DOI: 10.1016/j.frl.2023.104763
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612323011352
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2023.104763?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. Lin, Zih-Ying, 2021. "Investor attention and cryptocurrency performance," Finance Research Letters, Elsevier, vol. 40(C).
    2. Aslanidis, Nektarios & Bariviera, Aurelio F. & López, Óscar G., 2022. "The link between cryptocurrencies and Google Trends attention," Finance Research Letters, Elsevier, vol. 47(PA).
    3. Jin, Li & Myers, Stewart C., 2006. "R2 around the world: New theory and new tests," Journal of Financial Economics, Elsevier, vol. 79(2), pages 257-292, February.
    4. Bouri, Elie & Gabauer, David & Gupta, Rangan & Tiwari, Aviral Kumar, 2021. "Volatility connectedness of major cryptocurrencies: The role of investor happiness," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
    5. Ho-Chuan (River) Huang & Yi-Chen Lin & Chih-Chuan Yeh, 2012. "An appropriate test of the Kuznets hypothesis," Applied Economics Letters, Taylor & Francis Journals, vol. 19(1), pages 47-51, January.
    6. Zhang, Lan & Mykland, Per A. & Ait-Sahalia, Yacine, 2005. "A Tale of Two Time Scales: Determining Integrated Volatility With Noisy High-Frequency Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1394-1411, December.
    7. Jo Thori Lind & Halvor Mehlum, 2010. "With or Without U? The Appropriate Test for a U‐Shaped Relationship," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(1), pages 109-118, February.
    8. Shen, Dehua & Urquhart, Andrew & Wang, Pengfei, 2019. "Does twitter predict Bitcoin?," Economics Letters, Elsevier, vol. 174(C), pages 118-122.
    9. Naeem, Muhammad Abubakr & Mbarki, Imen & Shahzad, Syed Jawad Hussain, 2021. "Predictive role of online investor sentiment for cryptocurrency market: Evidence from happiness and fears," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 496-514.
    10. Lin, Xudong & Meng, Yiqun & Zhu, Hao, 2023. "How connected is the crypto market risk to investor sentiment?," Finance Research Letters, Elsevier, vol. 56(C).
    11. Koch, Sophia & Dimpfl, Thomas, 2023. "Attention and retail investor herding in cryptocurrency markets," Finance Research Letters, Elsevier, vol. 51(C).
    12. Milunovich, George & Lee, Seung Ah, 2022. "Measuring the impact of digital exchange cyberattacks on Bitcoin Returns," Economics Letters, Elsevier, vol. 221(C).
    13. Ma, Yu & Luan, Zhiqian, 2022. "Ethereum synchronicity, upside volatility and Bitcoin crash risk," Finance Research Letters, Elsevier, vol. 46(PA).
    14. Ole E. Barndorff-Nielsen & Neil Shephard, 2004. "Econometric Analysis of Realized Covariation: High Frequency Based Covariance, Regression, and Correlation in Financial Economics," Econometrica, Econometric Society, vol. 72(3), pages 885-925, May.
    15. Mokni, Khaled & Bouteska, Ahmed & Nakhli, Mohamed Sahbi, 2022. "Investor sentiment and Bitcoin relationship: A quantile-based analysis," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    16. Katsiampa, Paraskevi, 2019. "Volatility co-movement between Bitcoin and Ether," Finance Research Letters, Elsevier, vol. 30(C), pages 221-227.
    17. Kraaijeveld, Olivier & De Smedt, Johannes, 2020. "The predictive power of public Twitter sentiment for forecasting cryptocurrency prices," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
    18. Bourghelle, David & Jawadi, Fredj & Rozin, Philippe, 2022. "Do collective emotions drive bitcoin volatility? A triple regime-switching vector approach," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 294-306.
    19. Baur, Dirk G. & Dimpfl, Thomas, 2018. "Asymmetric volatility in cryptocurrencies," Economics Letters, Elsevier, vol. 173(C), pages 148-151.
    20. 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.
    21. 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.
    22. Gaies, Brahim & Nakhli, Mohamed Sahbi & Sahut, Jean-Michel & Schweizer, Denis, 2023. "Interactions between investors’ fear and greed sentiment and Bitcoin prices," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    23. Tian, Zengrui & Zhu, Bingsheng & Lu, Yuzhong, 2023. "The governance of non-state shareholders and corporate ESG: Empirical evidence from China," Finance Research Letters, Elsevier, vol. 56(C).
    24. Yukun Liu & Aleh Tsyvinski, 2021. "Risks and Returns of Cryptocurrency," The Review of Financial Studies, Society for Financial Studies, vol. 34(6), pages 2689-2727.
    25. Ren, Boru & Lucey, Brian, 2022. "Do clean and dirty cryptocurrency markets herd differently?," Finance Research Letters, Elsevier, vol. 47(PB).
    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. Wang, Jying-Nan & Vigne, Samuel A. & Liu, Hung-Chun & Hsu, Yuan-Teng, 2024. "Hacks and the price synchronicity of bitcoin and ether," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 294-299.
    2. Wang, Jying-Nan & Vigne, Samuel A. & Liu, Hung-Chun & Hsu, Yuan-Teng, 2024. "Divergent jump characteristics in brown and green cryptocurrencies: The role of energy-related uncertainty," Energy Economics, Elsevier, vol. 138(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. Wang, Jying-Nan & Vigne, Samuel A. & Liu, Hung-Chun & Hsu, Yuan-Teng, 2024. "Divergent jump characteristics in brown and green cryptocurrencies: The role of energy-related uncertainty," Energy Economics, Elsevier, vol. 138(C).
    2. Koch, Sophia & Dimpfl, Thomas, 2023. "Attention and retail investor herding in cryptocurrency markets," Finance Research Letters, Elsevier, vol. 51(C).
    3. Wang, Jying-Nan & Vigne, Samuel A. & Liu, Hung-Chun & Hsu, Yuan-Teng, 2024. "Hacks and the price synchronicity of bitcoin and ether," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 294-299.
    4. Ştefan Cristian Gherghina & Liliana Nicoleta Simionescu, 2023. "Exploring the asymmetric effect of COVID-19 pandemic news on the cryptocurrency market: evidence from nonlinear autoregressive distributed lag approach and frequency domain causality," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-58, December.
    5. Ahmed, Walid M.A., 2022. "Robust drivers of Bitcoin price movements: An extreme bounds analysis," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    6. Dunbar, Kwamie & Owusu-Amoako, Johnson, 2023. "Predictability of crypto returns: The impact of trading behavior," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    7. Smales, L.A., 2022. "Investor attention in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 79(C).
    8. Aurelio F. Bariviera & Ignasi Merediz‐Solà, 2021. "Where Do We Stand In Cryptocurrencies Economic Research? A Survey Based On Hybrid Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 377-407, April.
    9. Bouteska, Ahmed & Mefteh-Wali, Salma & Dang, Trung, 2022. "Predictive power of investor sentiment for Bitcoin returns: Evidence from COVID-19 pandemic," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    10. Banerjee, Ameet Kumar & Akhtaruzzaman, Md & Dionisio, Andreia & Almeida, Dora & Sensoy, Ahmet, 2022. "Nonlinear nexus between cryptocurrency returns and COVID-19 news sentiment," Journal of Behavioral and Experimental Finance, Elsevier, vol. 36(C).
    11. 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).
    12. Wang, Chen & Shen, Dehua & Li, Youwei, 2022. "Aggregate Investor Attention and Bitcoin Return: The Long Short-term Memory Networks Perspective," Finance Research Letters, Elsevier, vol. 49(C).
    13. 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).
    14. Aslanidis, Nektarios & Bariviera, Aurelio F. & Savva, Christos S., 2024. "Do online attention and sentiment affect cryptocurrencies’ correlations?," Research in International Business and Finance, Elsevier, vol. 71(C).
    15. Bourghelle, David & Jawadi, Fredj & Rozin, Philippe, 2022. "Do collective emotions drive bitcoin volatility? A triple regime-switching vector approach," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 294-306.
    16. Yae, James & Tian, George Zhe, 2022. "Out-of-sample forecasting of cryptocurrency returns: A comprehensive comparison of predictors and algorithms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).
    17. Arun Narayanasamy & Humnath Panta & Rohit Agarwal, 2023. "Relations among Bitcoin Futures, Bitcoin Spot, Investor Attention, and Sentiment," JRFM, MDPI, vol. 16(11), pages 1-24, November.
    18. Fayssal Jamhamed & Franck Martin & Fabien Rondeau & Josué Thélissaint & Stéphane Tufféry, 2024. "Regime-Specific Dynamics and Informational Efficiency in Cryptomarkets: Evidence from Gaussian Mixture Models," Economics Working Paper Archive (University of Rennes & University of Caen) 2024-13, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.
    19. Ozdamar, Melisa & Sensoy, Ahmet & Akdeniz, Levent, 2022. "Retail vs institutional investor attention in the cryptocurrency market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    20. Parthajit Kayal & Purnima Rohilla, 2021. "Bitcoin in the economics and finance literature: a survey," SN Business & Economics, Springer, vol. 1(7), pages 1-21, July.

    More about this item

    Keywords

    Fear and greed index; Price synchronicity; U-shaped relationship; Cryptocurrency; Realized correlation;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:59:y:2024:i:c:s1544612323011352. 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.