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Time-Varying Nexus between Investor Sentiment and Cryptocurrency Market: New Insights from a Wavelet Coherence Framework

Author

Listed:
  • Hashem A. AlNemer

    (Department of Finance and Economics, College of Business, University of Jeddah, Asfan Road 2749, Jeddah 23890, Saudi Arabia)

  • Besma Hkiri

    (Department of Finance and Economics, College of Business, University of Jeddah, Asfan Road 2749, Jeddah 23890, Saudi Arabia)

  • Muhammed Asif Khan

    (Department of Management Sciences, University of Swabi, Khyber Pakhtunkhwa 23430, Pakistan)

Abstract

This study attempts to investigate the nexus between investor sentiment and cryptocurrencies prices. Our empirical investigation merges bivariate and multivariate wavelet tools to examine the investor sentiment nexus to inter-cryptocurrencies prices. The study outcomes show that the Sentix Investor Confidence index provides significant information in explaining long-term changes in Bitcoin and Litecoin prices. Moreover, the findings generated from the multiple wavelet coherence illustrate the simultaneous contribution of cryptocurrencies and the Sentix Investor Confidence index in explaining the Bitcoin index movement across frequencies and over horizons, especially during bubble burst periods. The study also suggests a time-dependent relationship of Bitcoin prices with alternative cryptocurrencies and the Sentix Investor Confidence index, mostly pronounced during the Bitcoin bubble. We discuss our results using GSV-based investor sentiment. Our findings remain robust and confirm the strong predictive power of investor sentiment in cryptocurrencies price movements over time and across scales.

Suggested Citation

  • Hashem A. AlNemer & Besma Hkiri & Muhammed Asif Khan, 2021. "Time-Varying Nexus between Investor Sentiment and Cryptocurrency Market: New Insights from a Wavelet Coherence Framework," JRFM, MDPI, vol. 14(6), pages 1-19, June.
    • Handle: RePEc:gam:jjrfmx:v:14:y:2021:i:6:p:275-:d:577199
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    References listed on IDEAS

    as
    1. Wolfgang Karl Härdle & Campbell R Harvey & Raphael C G Reule, 2020. "Understanding Cryptocurrencies," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 181-208.
    2. Fang, Libing & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2019. "Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin?," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 29-36.
    3. Bouoiyour, Jamal & Selmi, Refk & Tiwari, Aviral Kumar & Shahbaz, Muhammad, 2015. "The nexus between oil price and Russia's real exchange rate: Better paths via unconditional vs conditional analysis," Energy Economics, Elsevier, vol. 51(C), pages 54-66.
    4. Gao, Zhenyu & Ren, Haohan & Zhang, Bohui, 2020. "Googling Investor Sentiment around the World," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 55(2), pages 549-580, March.
    5. Baig, Ahmed & Blau, Benjamin M. & Sabah, Nasim, 2019. "Price clustering and sentiment in bitcoin," Finance Research Letters, Elsevier, vol. 29(C), pages 111-116.
    6. 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.
    7. Bouoiyour, Jamal & Selmi, Refk & Tiwari, Aviral Kumar & Shahbaz, Muhammad, 2015. "The nexus between oil price and Russia's real exchange rate: Better paths via unconditional vs conditional analysis," Energy Economics, Elsevier, vol. 51(C), pages 54-66.
    8. Ross C Phillips & Denise Gorse, 2018. "Cryptocurrency price drivers: Wavelet coherence analysis revisited," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-21, April.
    9. Ciaian, Pavel & Rajcaniova, Miroslava & Kancs, d'Artis, 2018. "Virtual relationships: Short- and long-run evidence from BitCoin and altcoin markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 173-195.
    10. David Yermack, 2013. "Is Bitcoin a Real Currency? An economic appraisal," NBER Working Papers 19747, National Bureau of Economic Research, Inc.
    11. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
    12. Gurdgiev, Constantin & O’Loughlin, Daniel, 2020. "Herding and anchoring in cryptocurrency markets: Investor reaction to fear and uncertainty," Journal of Behavioral and Experimental Finance, Elsevier, vol. 25(C).
    13. Conlon, Thomas & McGee, Richard, 2020. "Safe haven or risky hazard? Bitcoin during the Covid-19 bear market," Finance Research Letters, Elsevier, vol. 35(C).
    14. Nguyen, Thai Vu Hong & Nguyen, Binh Thanh & Nguyen, Kien Son & Pham, Huy, 2019. "Asymmetric monetary policy effects on cryptocurrency markets," Research in International Business and Finance, Elsevier, vol. 48(C), pages 335-339.
    15. Aysan, Ahmet Faruk & Demir, Ender & Gozgor, Giray & Lau, Chi Keung Marco, 2019. "Effects of the geopolitical risks on Bitcoin returns and volatility," Research in International Business and Finance, Elsevier, vol. 47(C), pages 511-518.
    16. Ender Demir & Mehmet Huseyin Bilgin & Gokhan Karabulut & Asli Cansin Doker, 2020. "The relationship between cryptocurrencies and COVID-19 pandemic," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 10(3), pages 349-360, September.
    17. Corbet, Shaen & Lucey, Brian & Urquhart, Andrew & Yarovaya, Larisa, 2019. "Cryptocurrencies as a financial asset: A systematic analysis," International Review of Financial Analysis, Elsevier, vol. 62(C), pages 182-199.
    18. Corbet, Shaen & Meegan, Andrew & Larkin, Charles & Lucey, Brian & Yarovaya, Larisa, 2018. "Exploring the dynamic relationships between cryptocurrencies and other financial assets," Economics Letters, Elsevier, vol. 165(C), pages 28-34.
    19. Muhammad Ali Nasir & Toan Luu Duc Huynh & Sang Phu Nguyen & Duy Duong, 2019. "Forecasting cryptocurrency returns and volume using search engines," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-13, December.
    20. 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.
    21. Rognone, Lavinia & Hyde, Stuart & Zhang, S. Sarah, 2020. "News sentiment in the cryptocurrency market: An empirical comparison with Forex," International Review of Financial Analysis, Elsevier, vol. 69(C).
    22. Stavroyiannis, Stavros & Babalos, Vassilios & Bekiros, Stelios & Lahmiri, Salim & Uddin, Gazi Salah, 2019. "The high frequency multifractal properties of Bitcoin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 62-71.
    23. Corbet, Shaen & Larkin, Charles & Lucey, Brian, 2020. "The contagion effects of the COVID-19 pandemic: Evidence from gold and cryptocurrencies," Finance Research Letters, Elsevier, vol. 35(C).
    24. Bariviera, Aurelio F., 2017. "The inefficiency of Bitcoin revisited: A dynamic approach," Economics Letters, Elsevier, vol. 161(C), pages 1-4.
    25. Vytautas Karalevicius & Niels Degrande & Jochen De Weerdt, 2018. "Using sentiment analysis to predict interday Bitcoin price movements," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 19(1), pages 56-75, December.
    26. Chu, Jeffrey & Zhang, Yuanyuan & Chan, Stephen, 2019. "The adaptive market hypothesis in the high frequency cryptocurrency market," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 221-231.
    27. Eom, Cheoljun & Kaizoji, Taisei & Kang, Sang Hoon & Pichl, Lukas, 2019. "Bitcoin and investor sentiment: Statistical characteristics and predictability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 511-521.
    28. Wolfgang Karl Hardle & Campbell R. Harvey & Raphael C. G. Reule, 2020. "Editorial: Understanding Cryptocurrencies," Papers 2007.14702, arXiv.org.
    29. Conghui Chen & Lanlan Liu & Ningru Zhao, 2020. "Fear Sentiment, Uncertainty, and Bitcoin Price Dynamics: The Case of COVID-19," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(10), pages 2298-2309, August.
    30. Joseph, Kissan & Babajide Wintoki, M. & Zhang, Zelin, 2011. "Forecasting abnormal stock returns and trading volume using investor sentiment: Evidence from online search," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1116-1127, October.
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    2. 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.
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    4. Osman, Myriam Ben & Urom, Christian & Guesmi, Khaled & Benkraiem, Ramzi, 2024. "Economic sentiment and the cryptocurrency market in the post-COVID-19 era," International Review of Financial Analysis, Elsevier, vol. 91(C).

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