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Comparing search-engine and social-media attentions in finance research: Evidence from cryptocurrencies

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  • Li, Yue
  • Goodell, John W.
  • Shen, Dehua

Abstract

There is considerable interest in the impact of investor attention on investment returns, especially for cryptocurrencies. However, previous research does not distinguish between search-engine attention and social-media forms of attention—even though this distinction is emphasized by marketing professionals. Professional marketers emphasize that attention is optimized by combinations of social-media and search-engine presence. We investigate the bi-directional causalities, and concomitant frequencies, between cryptocurrency returns and investor attention, comparing cryptocurrency sensitivity to Twitter tweets and the intensity of Google searches, as well as combinations of Twitter and Google. For 27 cryptocurrencies, we use a non-parametric wavelet Granger causality test to incorporate multiple time horizons. We also employ Diebold and Yilmaz spillover testing to assess respective pairwise influence between attention measures and respective cryptocurrencies. Results indicate a preponderance of bidirectional Granger causality for the great majority of cryptocurrencies, with the impact of Twitter on cryptocurrencies being shorter term. Consistent with expectations, we identify that bi-directional causalities, and spillovers, of cryptocurrencies with investor attention are significantly more evident for proxies of investor attention that are combinations of social media (Twitter) and search engine intensity (Google), rather than either one of these forms alone. Our results have applicability to a broad range of investor attention studies.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:reveco:v:75:y:2021:i:c:p:723-746
    DOI: 10.1016/j.iref.2021.05.003
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    as
    1. Mensi, Walid & Ur Rehman, Mobeen & Maitra, Debasish & Hamed Al-Yahyaee, Khamis & Sensoy, Ahmet, 2020. "Does bitcoin co-move and share risk with Sukuk and world and regional Islamic stock markets? Evidence using a time-frequency approach," Research in International Business and Finance, Elsevier, vol. 53(C).
    2. Urquhart, Andrew, 2018. "What causes the attention of Bitcoin?," Economics Letters, Elsevier, vol. 166(C), pages 40-44.
    3. Eross, Andrea & McGroarty, Frank & Urquhart, Andrew & Wolfe, Simon, 2019. "The intraday dynamics of bitcoin," Research in International Business and Finance, Elsevier, vol. 49(C), pages 71-81.
    4. Corbet, Shaen & Goodell, John W. & Günay, Samet, 2020. "Co-movements and spillovers of oil and renewable firms under extreme conditions: New evidence from negative WTI prices during COVID-19," Energy Economics, Elsevier, vol. 92(C).
    5. Piñeiro-Chousa, Juan & López-Cabarcos, M. Ángeles & Pérez-Pico, Ada María & Ribeiro-Navarrete, Belén, 2018. "Does social network sentiment influence the relationship between the S&P 500 and gold returns?," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 57-64.
    6. 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).
    7. Katsiampa, Paraskevi, 2019. "An empirical investigation of volatility dynamics in the cryptocurrency market," Research in International Business and Finance, Elsevier, vol. 50(C), pages 322-335.
    8. 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.
    9. Torun, Erdost & Chang, Tzu-Pu & Chou, Ray Y., 2020. "Causal relationship between spot and futures prices with multiple time horizons: A nonparametric wavelet Granger causality test," Research in International Business and Finance, Elsevier, vol. 52(C).
    10. Shen, Dehua & Urquhart, Andrew & Wang, Pengfei, 2019. "Does twitter predict Bitcoin?," Economics Letters, Elsevier, vol. 174(C), pages 118-122.
    11. Goodell, John W. & Huynh, Toan Luu Duc, 2020. "Did Congress trade ahead? Considering the reaction of US industries to COVID-19," Finance Research Letters, Elsevier, vol. 36(C).
    12. Zhang, Zuochao & Zhang, Yongjie & Shen, Dehua & Zhang, Wei, 2018. "The cross-correlations between online sentiment proxies: Evidence from Google Trends and Twitter," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 67-75.
    13. Diks, Cees & Panchenko, Valentyn, 2006. "A new statistic and practical guidelines for nonparametric Granger causality testing," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1647-1669.
    14. 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.
    15. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    16. 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.
    17. Xiaohui Gao & Tse-Chun Lin, 2015. "Do Individual Investors Treat Trading as a Fun and Exciting Gambling Activity? Evidence from Repeated Natural Experiments," The Review of Financial Studies, Society for Financial Studies, vol. 28(7), pages 2128-2166.
    18. Reboredo, Juan C. & Ugolini, Andrea, 2018. "The impact of Twitter sentiment on renewable energy stocks," Energy Economics, Elsevier, vol. 76(C), pages 153-169.
    19. 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).
    20. Tao Guo & Michael Finke & Barry Mulholland, 2015. "Investor attention and advisor social media interaction," Applied Economics Letters, Taylor & Francis Journals, vol. 22(4), pages 261-265, March.
    21. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Filis, George, 2014. "Dynamic spillovers of oil price shocks and economic policy uncertainty," Energy Economics, Elsevier, vol. 44(C), pages 433-447.
    22. Philippas, Dionisis & Rjiba, Hatem & Guesmi, Khaled & Goutte, Stéphane, 2019. "Media attention and Bitcoin prices," Finance Research Letters, Elsevier, vol. 30(C), pages 37-43.
    23. Omane-Adjepong, Maurice & Alagidede, Imhotep Paul, 2019. "Multiresolution analysis and spillovers of major cryptocurrency markets," Research in International Business and Finance, Elsevier, vol. 49(C), pages 191-206.
    24. 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.
    25. Conlon, Thomas & McGee, Richard, 2020. "Safe haven or risky hazard? Bitcoin during the Covid-19 bear market," Finance Research Letters, Elsevier, vol. 35(C).
    26. Li, Sufang & Zhang, Hu & Yuan, Di, 2019. "Investor attention and crude oil prices: Evidence from nonlinear Granger causality tests," Energy Economics, Elsevier, vol. 84(C).
    27. Goodell, John W. & Goutte, Stephane, 2021. "Co-movement of COVID-19 and Bitcoin: Evidence from wavelet coherence analysis," Finance Research Letters, Elsevier, vol. 38(C).
    28. Huang, Shiyang & Huang, Yulin & Lin, Tse-Chun, 2019. "Attention allocation and return co-movement: Evidence from repeated natural experiments," Journal of Financial Economics, Elsevier, vol. 132(2), pages 369-383.
    29. 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.
    30. Xiang, Zheng & Gretzel, Ulrike, 2010. "Role of social media in online travel information search," Tourism Management, Elsevier, vol. 31(2), pages 179-188.
    31. Wilson, G. Tunnicliffe, 1978. "A convergence theorem for spectral factorization," Journal of Multivariate Analysis, Elsevier, vol. 8(2), pages 222-232, June.
    32. Katsiampa, Paraskevi & Corbet, Shaen & Lucey, Brian, 2019. "High frequency volatility co-movements in cryptocurrency markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 62(C), pages 35-52.
    33. Hu, Yitong & Li, Xiao & Goodell, John W. & Shen, Dehua, 2021. "Investor attention shocks and stock co-movement: Substitution or reinforcement?," International Review of Financial Analysis, Elsevier, vol. 73(C).
    34. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    35. Kyriazis, Nikolaos & Papadamou, Stephanos & Corbet, Shaen, 2020. "A systematic review of the bubble dynamics of cryptocurrency prices," Research in International Business and Finance, Elsevier, vol. 54(C).
    36. Benhmad, François, 2012. "Modeling nonlinear Granger causality between the oil price and U.S. dollar: A wavelet based approach," Economic Modelling, Elsevier, vol. 29(4), pages 1505-1514.
    37. Goodell, John W. & Goutte, Stephane, 2021. "Diversifying equity with cryptocurrencies during COVID-19," International Review of Financial Analysis, Elsevier, vol. 76(C).
    38. Katsiampa, Paraskevi & Corbet, Shaen & Lucey, Brian, 2019. "Volatility spillover effects in leading cryptocurrencies: A BEKK-MGARCH analysis," Finance Research Letters, Elsevier, vol. 29(C), pages 68-74.
    39. François Benhmad, 2012. "Modeling Nonlinear Granger Causality between the Oil price and U.S Dollar," Post-Print hal-03062497, HAL.
    40. Zhaunerchyk, Katsiaryna & Haghighi, Afshin & Oliver, Barry, 2020. "Distraction effects on stock return co-movements: Confirmation from the Shenzhen and Shanghai stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
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    Cited by:

    1. Meng, Yongqiang & Goodell, John W. & Shen, Dehua, 2023. "Information shocks and investor underreaction: Evidence from the Bitcoin market," Finance Research Letters, Elsevier, vol. 56(C).
    2. 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).
    3. Wu, Chunying & Xiong, Xiong & Gao, Ya & Zhang, Jin, 2022. "Does social media distort price discovery? Evidence from rumor clarifications," Research in International Business and Finance, Elsevier, vol. 62(C).
    4. Corbet, Shaen & Goodell, John W., 2022. "The reputational contagion effects of ransomware attacks," Finance Research Letters, Elsevier, vol. 47(PB).
    5. Wu, Wanshan & Tiwari, Aviral Kumar & Gozgor, Giray & Leping, Huang, 2021. "Does economic policy uncertainty affect cryptocurrency markets? Evidence from Twitter-based uncertainty measures," Research in International Business and Finance, Elsevier, vol. 58(C).
    6. Peng‐Fei Dai & John W. Goodell & Luu Duc Toan Huynh & Zhifeng Liu & Shaen Corbet, 2023. "Understanding the transmission of crash risk between cryptocurrency and equity markets," The Financial Review, Eastern Finance Association, vol. 58(3), pages 539-573, August.
    7. Chengying He & Yong Li & Tianqi Wang & Salman Ali Shah, 2024. "Is cryptocurrency a hedging tool during economic policy uncertainty? An empirical investigation," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.
    8. Gang Chu & John W. Goodell & Dehua Shen & Yongjie Zhang, 2022. "Machine learning to establish proxies for investor attention: evidence of improved stock-return prediction," Annals of Operations Research, Springer, vol. 318(1), pages 103-128, November.
    9. Hajek, Petr & Hikkerova, Lubica & Sahut, Jean-Michel, 2023. "How well do investor sentiment and ensemble learning predict Bitcoin prices?," Research in International Business and Finance, Elsevier, vol. 64(C).
    10. 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).
    11. Adedeji Daniel Gbadebo, 2023. "Dynamic Asymmetric Causality of Bitcoin’s Price-Volume Relation," SAGE Open, , vol. 13(4), pages 21582440231, December.
    12. Anastasiou, Dimitrios & Bragoudakis, Zacharias & Giannoulakis, Stelios, 2021. "Perceived vs actual financial crisis and bank credit standards: Is there any indication of self-fulfilling prophecy?," Research in International Business and Finance, Elsevier, vol. 58(C).
    13. Xu, Kewei & Xiong, Xiong & Li, Xiao, 2021. "The maturity effect of stock index futures: Speculation or carry arbitrage?," Research in International Business and Finance, Elsevier, vol. 58(C).
    14. Tong, Zezheng & Goodell, John W. & Shen, Dehua, 2022. "Assessing causal relationships between cryptocurrencies and investor attention: New results from transfer entropy methodology," Finance Research Letters, Elsevier, vol. 50(C).
    15. Kyriazis, Nikolaos & Papadamou, Stephanos & Tzeremes, Panayiotis & Corbet, Shaen, 2023. "The differential influence of social media sentiment on cryptocurrency returns and volatility during COVID-19," The Quarterly Review of Economics and Finance, Elsevier, vol. 89(C), pages 307-317.
    16. Wang, Ping & Han, Wei & Huang, Chengcheng & Duong, Duy, 2022. "Forecasting realised volatility from search volume and overnight sentiment: Evidence from China," Research in International Business and Finance, Elsevier, vol. 62(C).
    17. Chu, Gang & Li, Xiao & Zhang, Yongjie, 2022. "Information demand and net selling around earnings announcement," Research in International Business and Finance, Elsevier, vol. 59(C).
    18. Goodell, John W. & Alon, Ilan & Chiaramonte, Laura & Dreassi, Alberto & Paltrinieri, Andrea & Piserà, Stefano, 2023. "Risk substitution in cryptocurrencies: Evidence from BRICS announcements," Emerging Markets Review, Elsevier, vol. 54(C).
    19. Jia, Boxiang & Shen, Dehua & Zhang, Wei, 2022. "Extreme sentiment and herding: Evidence from the cryptocurrency market," Research in International Business and Finance, Elsevier, vol. 63(C).
    20. Yongjie Zhang & Yue Li & Dehua Shen, 2022. "Investor Attention and the Carbon Emission Markets in China: A Nonparametric Wavelet-Based Causality Test," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 29(1), pages 123-137, March.
    21. Toan Luu Duc Huynh, 2023. "When Elon Musk Changes his Tone, Does Bitcoin Adjust Its Tune?," Computational Economics, Springer;Society for Computational Economics, vol. 62(2), pages 639-661, August.
    22. Ajithakumari Vijayappan Nair Biju & Ann Susan Thomas, 2023. "Uncertainties and ambivalence in the crypto market: an urgent need for a regional crypto regulation," SN Business & Economics, Springer, vol. 3(8), pages 1-21, August.
    23. Goodell, John W. & Kumar, Satish & Li, Xiao & Pattnaik, Debidutta & Sharma, Anuj, 2022. "Foundations and research clusters in investor attention: Evidence from bibliometric and topic modelling analysis," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 511-529.
    24. Zhang, Jiahang & Zhang, Chi, 2022. "Do cryptocurrency markets react to issuer sentiments? Evidence from Twitter," Research in International Business and Finance, Elsevier, vol. 61(C).
    25. 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).

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    More about this item

    Keywords

    Cryptocurrencies; Investor attention; Granger causality; Social media; Twitter; Google; Wavelet testing;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G4 - Financial Economics - - Behavioral Finance

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