IDEAS home Printed from https://ideas.repec.org/a/eee/ecofin/v60y2022ics1062940822000171.html
   My bibliography  Save this article

Investor sentiment and Bitcoin relationship: A quantile-based analysis

Author

Listed:
  • Mokni, Khaled
  • Bouteska, Ahmed
  • Nakhli, Mohamed Sahbi

Abstract

This paper applies a quantile-based analysis to investigate the causal relationships between Bitcoin and investor sentiment by considering the possible effects of the ongoing COVID-19 pandemic. Such an analysis allows investigating the predictive power of investor sentiment (Bitcoin) on Bitcoin (investor sentiment) at different levels of the distributions. Results emphasize that only Bitcoin returns/volatility have significant predictive power on the investor sentiment whether investors are fear or greed before and over the COVID-19 period. Moreover, the COVID-19 crisis has no effect on the causal relationship between the two variables. Further analysis shows an asymmetric causality observed only during the pandemic period. Furthermore, the quantile autoregressive regression model shows a significant positive relationship between investor sentiment and Bitcoin returns.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:ecofin:v:60:y:2022:i:c:s1062940822000171
    DOI: 10.1016/j.najef.2022.101657
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062940822000171
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.najef.2022.101657?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. Philippas, Dionisis & Rjiba, Hatem & Guesmi, Khaled & Goutte, Stéphane, 2019. "Media attention and Bitcoin prices," Finance Research Letters, Elsevier, vol. 30(C), pages 37-43.
    2. Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch & Mark E. Wohar, 2018. "Terror attacks and stock-market fluctuations: evidence based on a nonparametric causality-in-quantiles test for the G7 countries," The European Journal of Finance, Taylor & Francis Journals, vol. 24(4), pages 333-346, March.
    3. Mehmet Balcilar & Rangan Gupta & Clement Kyei & Mark E. Wohar, 2016. "Does Economic Policy Uncertainty Predict Exchange Rate Returns and Volatility? Evidence from a Nonparametric Causality-in-Quantiles Test," Open Economies Review, Springer, vol. 27(2), pages 229-250, April.
    4. Yu, Miao, 2019. "Forecasting Bitcoin volatility: The role of leverage effect and uncertainty," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 533(C).
    5. Imran Yousaf & Shoaib Ali, 2020. "Discovering interlinkages between major cryptocurrencies using high-frequency data: new evidence from COVID-19 pandemic," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-18, December.
    6. Mokni, Khaled & Youssef, Manel & Ajmi, Ahdi Noomen, 2022. "COVID-19 pandemic and economic policy uncertainty: The first test on the hedging and safe haven properties of cryptocurrencies," Research in International Business and Finance, Elsevier, vol. 60(C).
    7. Li, Zijian & Meng, Qiaoyu, 2022. "Time and frequency connectedness and portfolio diversification between cryptocurrencies and renewable energy stock markets during COVID-19," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    8. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    9. Chemkha, Rahma & BenSaïda, Ahmed & Ghorbel, Ahmed & Tayachi, Tahar, 2021. "Hedge and safe haven properties during COVID-19: Evidence from Bitcoin and gold," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 71-85.
    10. Zhi Da & Joseph Engelberg & Pengjie Gao, 2015. "Editor's Choice The Sum of All FEARS Investor Sentiment and Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 28(1), pages 1-32.
    11. Sun, Licheng & Najand, Mohammad & Shen, Jiancheng, 2016. "Stock return predictability and investor sentiment: A high-frequency perspective," Journal of Banking & Finance, Elsevier, vol. 73(C), pages 147-164.
    12. Mokni, Khaled, 2021. "When, where, and how economic policy uncertainty predicts Bitcoin returns and volatility? A quantiles-based analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 65-73.
    13. Shaen Corbet & Charles Larkin & Brian M. Lucey & Andrew Meegan & Larisa Yarovaya, 2020. "The impact of macroeconomic news on Bitcoin returns," The European Journal of Finance, Taylor & Francis Journals, vol. 26(14), pages 1396-1416, September.
    14. Renault, Thomas, 2017. "Intraday online investor sentiment and return patterns in the U.S. stock market," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 25-40.
    15. Urquhart, Andrew, 2018. "What causes the attention of Bitcoin?," Economics Letters, Elsevier, vol. 166(C), pages 40-44.
    16. Stambaugh, Robert F. & Yu, Jianfeng & Yuan, Yu, 2012. "The short of it: Investor sentiment and anomalies," Journal of Financial Economics, Elsevier, vol. 104(2), pages 288-302.
    17. Conlon, Thomas & McGee, Richard, 2020. "Safe haven or risky hazard? Bitcoin during the Covid-19 bear market," Finance Research Letters, Elsevier, vol. 35(C).
    18. Alexander Guzmán & Christian Pinto-Gutiérrez & María-Andrea Trujillo, 2021. "Trading Cryptocurrencies as a Pandemic Pastime: COVID-19 Lockdowns and Bitcoin Volume," Mathematics, MDPI, vol. 9(15), pages 1-15, July.
    19. Diego García, 2013. "Sentiment during Recessions," Journal of Finance, American Finance Association, vol. 68(3), pages 1267-1300, June.
    20. Roger Koenker & Zhijie Xiao, 2004. "Unit Root Quantile Autoregression Inference," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 775-787, January.
    21. Thomas Renault, 2017. "Intraday online investor sentiment and return patterns in the U.S. stock market," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03205113, HAL.
    22. Shiller, Robert J, 1981. "Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?," American Economic Review, American Economic Association, vol. 71(3), pages 421-436, June.
    23. Guégan, Dominique & Renault, Thomas, 2021. "Does investor sentiment on social media provide robust information for Bitcoin returns predictability?," Finance Research Letters, Elsevier, vol. 38(C).
    24. Gustavo Grullon, 2004. "Advertising, Breadth of Ownership, and Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 17(2), pages 439-461.
    25. Kinateder, Harald & Papavassiliou, Vassilios G., 2021. "Calendar effects in Bitcoin returns and volatility," Finance Research Letters, Elsevier, vol. 38(C).
    26. Dastgir, Shabbir & Demir, Ender & Downing, Gareth & Gozgor, Giray & Lau, Chi Keung Marco, 2019. "The causal relationship between Bitcoin attention and Bitcoin returns: Evidence from the Copula-based Granger causality test," Finance Research Letters, Elsevier, vol. 28(C), pages 160-164.
    27. Nikolaos Antonakakis & Mehmet Balcilar & Rangan Gupta & Clement Kyei, 2016. "Components of Economic Policy Uncertainty and Predictability of US Stock Returns and Volatility: Evidence from a Nonparametric Causality-in-Quantile Approach," Working Papers 201639, University of Pretoria, Department of Economics.
    28. Sabah, Nasim, 2020. "Cryptocurrency accepting venues, investor attention, and volatility," Finance Research Letters, Elsevier, vol. 36(C).
    29. 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.
    30. Paul C. Tetlock & Maytal Saar‐Tsechansky & Sofus Macskassy, 2008. "More Than Words: Quantifying Language to Measure Firms' Fundamentals," Journal of Finance, American Finance Association, vol. 63(3), pages 1437-1467, June.
    31. Mehmet Balcilar & Stelios Bekiros & Rangan Gupta, 2017. "The role of news-based uncertainty indices in predicting oil markets: a hybrid nonparametric quantile causality method," Empirical Economics, Springer, vol. 53(3), pages 879-889, November.
    32. Shen, Dehua & Urquhart, Andrew & Wang, Pengfei, 2019. "Does twitter predict Bitcoin?," Economics Letters, Elsevier, vol. 174(C), pages 118-122.
    33. Chen, Rongda & Qian, Qian & Jin, Chenglu & Xu, Min & Song, Qiping, 2020. "Investor attention on internet financial markets," Finance Research Letters, Elsevier, vol. 36(C).
    34. Hasan, Md. Bokhtiar & Hassan, M. Kabir & Rashid, Md. Mamunur & Alhenawi, Yasser, 2021. "Are safe haven assets really safe during the 2008 global financial crisis and COVID-19 pandemic?," Global Finance Journal, Elsevier, vol. 50(C).
    35. 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).
    36. 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.
    37. Akyildirim, Erdinc & Corbet, Shaen & Lucey, Brian & Sensoy, Ahmet & Yarovaya, Larisa, 2020. "The relationship between implied volatility and cryptocurrency returns," Finance Research Letters, Elsevier, vol. 33(C).
    38. Ben Khelifa, Soumaya & Guesmi, Khaled & Urom, Christian, 2021. "Exploring the relationship between cryptocurrencies and hedge funds during COVID-19 crisis," International Review of Financial Analysis, Elsevier, vol. 76(C).
    39. Choi, Hyungeun, 2021. "Investor attention and bitcoin liquidity: Evidence from bitcoin tweets," Finance Research Letters, Elsevier, vol. 39(C).
    40. Dwita Mariana, Christy & Ekaputra, Irwan Adi & Husodo, Zaäfri Ananto, 2021. "Are Bitcoin and Ethereum safe-havens for stocks during the COVID-19 pandemic?," Finance Research Letters, Elsevier, vol. 38(C).
    41. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    42. Huang, Yingying & Duan, Kun & Mishra, Tapas, 2021. "Is Bitcoin really more than a diversifier? A pre- and post-COVID-19 analysis," Finance Research Letters, Elsevier, vol. 43(C).
    43. 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.
    44. Lily Fang & Joel Peress, 2009. "Media Coverage and the Cross‐section of Stock Returns," Journal of Finance, American Finance Association, vol. 64(5), pages 2023-2052, October.
    45. A. Craig MacKinlay, 1997. "Event Studies in Economics and Finance," Journal of Economic Literature, American Economic Association, vol. 35(1), pages 13-39, March.
    46. Jeong, Kiho & Härdle, Wolfgang K. & Song, Song, 2012. "A Consistent Nonparametric Test For Causality In Quantile," Econometric Theory, Cambridge University Press, vol. 28(4), pages 861-887, August.
    47. Nishiyama, Yoshihiko & Hitomi, Kohtaro & Kawasaki, Yoshinori & Jeong, Kiho, 2011. "A consistent nonparametric test for nonlinear causality—Specification in time series regression," Journal of Econometrics, Elsevier, vol. 165(1), pages 112-127.
    48. Gaies, Brahim & Nakhli, Mohamed Sahbi & Sahut, Jean Michel & Guesmi, Khaled, 2021. "Is Bitcoin rooted in confidence? – Unraveling the determinants of globalized digital currencies," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    49. Ibikunle, Gbenga & McGroarty, Frank & Rzayev, Khaladdin, 2020. "More heat than light: Investor attention and bitcoin price discovery," International Review of Financial Analysis, Elsevier, vol. 69(C).
    50. David Garcia & Frank Schweitzer, 2015. "Social signals and algorithmic trading of Bitcoin," Papers 1506.01513, arXiv.org, revised Sep 2015.
    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. Dhasmana, Samriddhi & Ghosh, Sajal & Kanjilal, Kakali, 2023. "Does investor sentiment influence ESG stock performance? Evidence from India," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    2. Gao, Zhenbin & Zhang, Jie, 2023. "The fluctuation correlation between investor sentiment and stock index using VMD-LSTM: Evidence from China stock market," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).
    3. 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.
    4. 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).
    5. Lin, Xudong & Meng, Yiqun & Zhu, Hao, 2023. "How connected is the crypto market risk to investor sentiment?," Finance Research Letters, Elsevier, vol. 56(C).
    6. Yu‐Lun Chen & J. Jimmy Yang, 2024. "Time‐varying price discovery in regular and microbitcoin futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(1), pages 103-121, January.
    7. Bouteska, Ahmed & Hajek, Petr & Abedin, Mohammad Zoynul & Dong, Yizhe, 2023. "Effect of twitter investor engagement on cryptocurrencies during the COVID-19 pandemic," Research in International Business and Finance, Elsevier, vol. 64(C).
    8. 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).

    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. 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.
    2. 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).
    3. Dias, Ishanka K. & Fernando, J.M. Ruwani & Fernando, P. Narada D., 2022. "Does investor sentiment predict bitcoin return and volatility? A quantile regression approach," International Review of Financial Analysis, Elsevier, vol. 84(C).
    4. 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).
    5. Zeitun, Rami & Rehman, Mobeen Ur & Ahmad, Nasir & Vo, Xuan Vinh, 2023. "The impact of Twitter-based sentiment on US sectoral returns," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    6. 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).
    7. ?ikolaos A. Kyriazis, 2021. "Impacts of Stock Indices, Oil, and Twitter Sentiment on Major Cryptocurrencies during the COVID-19 First Wave," Bulletin of Applied Economics, Risk Market Journals, vol. 8(2), pages 133-146.
    8. 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).
    9. Yousaf, Imran & Youssef, Manel & Goodell, John W., 2022. "Quantile connectedness between sentiment and financial markets: Evidence from the S&P 500 twitter sentiment index," International Review of Financial Analysis, Elsevier, vol. 83(C).
    10. Marmora, Paul, 2022. "Does monetary policy fuel bitcoin demand? Event-study evidence from emerging markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    11. Li, Yue & Goodell, John W. & Shen, Dehua, 2021. "Comparing search-engine and social-media attentions in finance research: Evidence from cryptocurrencies," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 723-746.
    12. Szymon Lis, 2022. "Investor Sentiment in Asset Pricing Models: A Review," Working Papers 2022-14, Faculty of Economic Sciences, University of Warsaw.
    13. Guofu Zhou, 2018. "Measuring Investor Sentiment," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 239-259, November.
    14. Gaies, Brahim & Nakhli, Mohamed Sahbi & Sahut, Jean Michel & Guesmi, Khaled, 2021. "Is Bitcoin rooted in confidence? – Unraveling the determinants of globalized digital currencies," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    15. Feng, Hao & Gao, Da & Duan, Kun & Urquhart, Andrew, 2023. "Does Bitcoin affect decomposed oil shocks differently? Evidence from a quantile-based framework," International Review of Financial Analysis, Elsevier, vol. 89(C).
    16. Al Guindy, Mohamed, 2021. "Cryptocurrency price volatility and investor attention," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 556-570.
    17. Li, Xiao, 2021. "Does Chinese investor sentiment predict Asia-pacific stock markets? Evidence from a nonparametric causality-in-quantiles test," Finance Research Letters, Elsevier, vol. 38(C).
    18. Mohammad Alomari & Abdel Razzaq Al rababa’a & Ghaith El-Nader & Ahmad Alkhataybeh, 2021. "Who’s behind the wheel? The role of social and media news in driving the stock–bond correlation," Review of Quantitative Finance and Accounting, Springer, vol. 57(3), pages 959-1007, October.
    19. Daniele Ballinari & Simon Behrendt, 2021. "How to gauge investor behavior? A comparison of online investor sentiment measures," Digital Finance, Springer, vol. 3(2), pages 169-204, June.
    20. Smales, L.A., 2022. "Investor attention in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 79(C).

    More about this item

    Keywords

    Fear greed index; Bitcoin; Nonparametric causality; Quantiles; COVID-19;
    All these keywords.

    JEL classification:

    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets
    • 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

    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:ecofin:v:60:y:2022:i:c:s1062940822000171. 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/inca/620163 .

    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.