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Investor attention and cryptocurrency market liquidity: a double-edged sword

Author

Listed:
  • Shouyu Yao

    (Tianjin University)

  • Ahmet Sensoy

    (Bilkent University
    Lebanese American University)

  • Duc Khuong Nguyen

    (IPAG Business School
    Vietnam National University
    Prague University of Economics and Business)

  • Tong Li

    (Tianjin University)

Abstract

This paper explores the double-edged sword effect of investor attention on market liquidity. Based on the analysis on 597 cryptocurrencies from 2014 to 2020, our findings show that static investor attention improves cryptocurrency market liquidity over the next three months by attracting more investors into the market and stimulating buy and sell transactions. By contrast, abnormal attention persistently and negatively affects the liquidity and leads to excessive net buying pressure in the market and a crowded buyers’ market, resulting in a sharp deterioration of liquidity. Moreover, these effects intensify during low global economic policy uncertainty periods and for cryptocurrencies with small market capitalization and low idiosyncratic volatility. Overall, our results have important implications for investors, portfolio managers, and policymakers.

Suggested Citation

  • Shouyu Yao & Ahmet Sensoy & Duc Khuong Nguyen & Tong Li, 2024. "Investor attention and cryptocurrency market liquidity: a double-edged sword," Annals of Operations Research, Springer, vol. 334(1), pages 815-856, March.
  • Handle: RePEc:spr:annopr:v:334:y:2024:i:1:d:10.1007_s10479-022-04915-w
    DOI: 10.1007/s10479-022-04915-w
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    as
    1. Ruan, Xinfeng & Zhang, Jin E., 2016. "Investor attention and market microstructure," Economics Letters, Elsevier, vol. 149(C), pages 125-130.
    2. Alex Edmans & Vivian W. Fang & Emanuel Zur, 2013. "The Effect of Liquidity on Governance," The Review of Financial Studies, Society for Financial Studies, vol. 26(6), pages 1443-1482.
    3. Afonso, Gara, 2011. "Liquidity and congestion," Journal of Financial Intermediation, Elsevier, vol. 20(3), pages 324-360, July.
    4. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    5. 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.
    6. Chen, Yunsen & Xie, Yuan & You, Hong & Zhang, Yanan, 2018. "Does crackdown on corruption reduce stock price crash risk? Evidence from China," Journal of Corporate Finance, Elsevier, vol. 51(C), pages 125-141.
    7. Huang, Yuqin & Qiu, Huiyan & Wu, Zhiguo, 2016. "Local bias in investor attention: Evidence from China's Internet stock message boards," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 338-354.
    8. Peng, Lin, 2005. "Learning with Information Capacity Constraints," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 40(2), pages 307-329, June.
    9. Urquhart, Andrew, 2018. "What causes the attention of Bitcoin?," Economics Letters, Elsevier, vol. 166(C), pages 40-44.
    10. Sabrina T Howell & Marina Niessner & David Yermack & Jiang Wei, 2020. "Initial Coin Offerings: Financing Growth with Cryptocurrency Token Sales," The Review of Financial Studies, Society for Financial Studies, vol. 33(9), pages 3925-3974.
    11. Yao, Shouyu & Wang, Chunfeng & Cui, Xin & Fang, Zhenming, 2019. "Idiosyncratic skewness, gambling preference, and cross-section of stock returns: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 464-483.
    12. Albert S. Kyle & Anna A. Obizhaeva, 2016. "Market Microstructure Invariance: Empirical Hypotheses," Econometrica, Econometric Society, vol. 84, pages 1345-1404, July.
    13. Merton, Robert C, 1987. "A Simple Model of Capital Market Equilibrium with Incomplete Information," Journal of Finance, American Finance Association, vol. 42(3), pages 483-510, July.
    14. 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.
    15. Shen, Dehua & Urquhart, Andrew & Wang, Pengfei, 2019. "Does twitter predict Bitcoin?," Economics Letters, Elsevier, vol. 174(C), pages 118-122.
    16. Matthias Bank & Martin Larch & Georg Peter, 2011. "Google search volume and its influence on liquidity and returns of German stocks," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 25(3), pages 239-264, September.
    17. Köchling, Gerrit & Müller, Janis & Posch, Peter N., 2019. "Price delay and market frictions in cryptocurrency markets," Economics Letters, Elsevier, vol. 174(C), pages 39-41.
    18. Lin William Cong & Zhiguo He, 2019. "Blockchain Disruption and Smart Contracts," The Review of Financial Studies, Society for Financial Studies, vol. 32(5), pages 1754-1797.
    19. Peng, Lin & Xiong, Wei, 2006. "Investor attention, overconfidence and category learning," Journal of Financial Economics, Elsevier, vol. 80(3), pages 563-602, June.
    20. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    21. Makarov, Igor & Schoar, Antoinette, 2020. "Trading and arbitrage in cryptocurrency markets," LSE Research Online Documents on Economics 100409, London School of Economics and Political Science, LSE Library.
    22. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2006. "The Cross‐Section of Volatility and Expected Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 259-299, February.
    23. Takeda, Fumiko & Wakao, Takumi, 2014. "Google search intensity and its relationship with returns and trading volume of Japanese stocks," Pacific-Basin Finance Journal, Elsevier, vol. 27(C), pages 1-18.
    24. Cheng, Feiyang & Chiao, Chaoshin & Wang, Chunfeng & Fang, Zhenming & Yao, Shouyu, 2021. "Does retail investor attention improve stock liquidity? A dynamic perspective," Economic Modelling, Elsevier, vol. 94(C), pages 170-183.
    25. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    26. Alok Kumar, 2009. "Who Gambles in the Stock Market?," Journal of Finance, American Finance Association, vol. 64(4), pages 1889-1933, August.
    27. Erdinc Akyildirim & Ahmet Goncu & Ahmet Sensoy, 2021. "Prediction of cryptocurrency returns using machine learning," Annals of Operations Research, Springer, vol. 297(1), pages 3-36, February.
    28. Koutmos, Dimitrios, 2018. "Bitcoin returns and transaction activity," Economics Letters, Elsevier, vol. 167(C), pages 81-85.
    29. Ding, Rong & Hou, Wenxuan, 2015. "Retail investor attention and stock liquidity," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 37(C), pages 12-26.
    30. Campbell R. Harvey & Akhtar Siddique, 2000. "Conditional Skewness in Asset Pricing Tests," Journal of Finance, American Finance Association, vol. 55(3), pages 1263-1295, June.
    31. Sowmya Subramaniam & Madhumita Chakraborty, 2020. "Investor Attention and Cryptocurrency Returns: Evidence from Quantile Causality Approach," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 21(1), pages 103-115, January.
    32. 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).
    33. Philippas, Dionisis & Rjiba, Hatem & Guesmi, Khaled & Goutte, Stéphane, 2019. "Media attention and Bitcoin prices," Finance Research Letters, Elsevier, vol. 30(C), pages 37-43.
    34. Aouadi, Amal & Arouri, Mohamed & Teulon, Frédéric, 2013. "Investor attention and stock market activity: Evidence from France," Economic Modelling, Elsevier, vol. 35(C), pages 674-681.
    35. Makarov, Igor & Schoar, Antoinette, 2020. "Trading and arbitrage in cryptocurrency markets," Journal of Financial Economics, Elsevier, vol. 135(2), pages 293-319.
    36. Li, Yi & Urquhart, Andrew & Wang, Pengfei & Zhang, Wei, 2021. "MAX momentum in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 77(C).
    37. Scharnowski, Stefan, 2021. "Understanding Bitcoin liquidity," Finance Research Letters, Elsevier, vol. 38(C).
    38. Mitchell A. Petersen, 2009. "Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches," The Review of Financial Studies, Society for Financial Studies, vol. 22(1), pages 435-480, January.
    39. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
    40. Mondria, Jordi & Wu, Thomas & Zhang, Yi, 2010. "The determinants of international investment and attention allocation: Using internet search query data," Journal of International Economics, Elsevier, vol. 82(1), pages 85-95, September.
    41. Wei Zhang & Pengfei Wang, 2020. "Investor attention and the pricing of cryptocurrency market," Evolutionary and Institutional Economics Review, Springer, vol. 17(2), pages 445-468, July.
    42. Nadarajah, Saralees & Chu, Jeffrey, 2017. "On the inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 150(C), pages 6-9.
    43. Liu, Weiyi & Liang, Xuan & Cui, Guowei, 2020. "Common risk factors in the returns on cryptocurrencies," Economic Modelling, Elsevier, vol. 86(C), pages 299-305.
    44. Lin William Cong & Ye Li & Neng Wang, 2021. "Tokenomics: Dynamic Adoption and Valuation [The demand of liquid assets with uncertain lumpy expenditures]," The Review of Financial Studies, Society for Financial Studies, vol. 34(3), pages 1105-1155.
    45. Michael S. Drake & Darren T. Roulstone & Jacob R. Thornock, 2012. "Investor Information Demand: Evidence from Google Searches Around Earnings Announcements," Journal of Accounting Research, Wiley Blackwell, vol. 50(4), pages 1001-1040, September.
    46. Grobys, Klaus & Junttila, Juha, 2021. "Speculation and lottery-like demand in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    47. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," The Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    48. Adachi, Yuta & Masuda, Motoki & Takeda, Fumiko, 2017. "Google search intensity and its relationship to the returns and liquidity of Japanese startup stocks," Pacific-Basin Finance Journal, Elsevier, vol. 46(PB), pages 243-257.
    49. Li, Jun & Yu, Jianfeng, 2012. "Investor attention, psychological anchors, and stock return predictability," Journal of Financial Economics, Elsevier, vol. 104(2), pages 401-419.
    50. Gustavo Grullon, 2004. "Advertising, Breadth of Ownership, and Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 17(2), pages 439-461.
    51. 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.
    52. 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.
    53. Sabah, Nasim, 2020. "Cryptocurrency accepting venues, investor attention, and volatility," Finance Research Letters, Elsevier, vol. 36(C).
    54. Asparouhova, Elena & Bessembinder, Hendrik & Kalcheva, Ivalina, 2010. "Liquidity biases in asset pricing tests," Journal of Financial Economics, Elsevier, vol. 96(2), pages 215-237, May.
    55. Albert S. Kyle & Anna A. Obizhaeva, 2016. "Market Microstructure Invariance: Empirical Hypotheses," Econometrica, Econometric Society, vol. 84(4), pages 1345-1404, July.
    56. Joshua D. Coval & Tobias J. Moskowitz, 1999. "Home Bias at Home: Local Equity Preference in Domestic Portfolios," Journal of Finance, American Finance Association, vol. 54(6), pages 2045-2073, December.
    57. Choi, Hyungeun, 2021. "Investor attention and bitcoin liquidity: Evidence from bitcoin tweets," Finance Research Letters, Elsevier, vol. 39(C).
    58. Yao, Shouyu & Wang, Chunfeng & Fang, Zhenming & Chiao, Chaoshin, 2021. "MAX is not the max under the interference of daily price limits: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 348-369.
    59. Timothy King & Dimitrios Koutmos, 2021. "Herding and feedback trading in cryptocurrency markets," Annals of Operations Research, Springer, vol. 300(1), pages 79-96, May.
    60. Alessandra Cretarola & Gianna Figà-Talamanca, 2021. "Detecting bubbles in Bitcoin price dynamics via market exuberance," Annals of Operations Research, Springer, vol. 299(1), pages 459-479, April.
    61. Joel Hasbrouck, 2009. "Trading Costs and Returns for U.S. Equities: Estimating Effective Costs from Daily Data," Journal of Finance, American Finance Association, vol. 64(3), pages 1445-1477, June.
    62. C. Baek & M. Elbeck, 2015. "Bitcoins as an investment or speculative vehicle? A first look," Applied Economics Letters, Taylor & Francis Journals, vol. 22(1), pages 30-34, January.
    63. 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.
    64. Mark S. Seasholes & Ning Zhu, 2010. "Individual Investors and Local Bias," Journal of Finance, American Finance Association, vol. 65(5), pages 1987-2010, October.
    65. Cheng, Feiyang & Wang, Chunfeng & Chiao, Chaoshin & Yao, Shouyu & Fang, Zhenming, 2021. "Retail attention, retail trades, and stock price crash risk," Emerging Markets Review, Elsevier, vol. 49(C).
    66. Celeste, Valerio & Corbet, Shaen & Gurdgiev, Constantin, 2020. "Fractal dynamics and wavelet analysis: Deep volatility and return properties of Bitcoin, Ethereum and Ripple," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 310-324.
    67. 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.
    68. Baur, Dirk G. & Hong, KiHoon & Lee, Adrian D., 2018. "Bitcoin: Medium of exchange or speculative assets?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 54(C), pages 177-189.
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    More about this item

    Keywords

    Cryptocurrency markets; Investor attention; Liquidity; Investor trading behavior;
    All these keywords.

    JEL classification:

    • G30 - Financial Economics - - Corporate Finance and Governance - - - General
    • G34 - Financial Economics - - Corporate Finance and Governance - - - Mergers; Acquisitions; Restructuring; Corporate Governance

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