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A Socio-Finance Model: The Case of Bitcoin

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Abstract

This paper investigates the relations between multiple measures of investor sentiment and the returns, volatility, trading volume, and liquidity. Using both data outside and inside market, we find that the Bullishness from socio-finance model are significant related to future realized volatility and trading volume, similar to Tweet, which is thought to capture information of well-informed investors in Bitcoin market

Suggested Citation

  • Yongqiang Meng & Dehua Shen & Xiong Xiong & Jorgen Vitting Andersen, 2020. "A Socio-Finance Model: The Case of Bitcoin," Documents de travail du Centre d'Economie de la Sorbonne 20031, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    • Handle: RePEc:mse:cesdoc:20031
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    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. Leung, Henry & Ton, Thai, 2015. "The impact of internet stock message boards on cross-sectional returns of small-capitalization stocks," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 37-55.
    3. Li, Xiao & Shen, Dehua & Zhang, Wei, 2018. "Do Chinese internet stock message boards convey firm-specific information?," Pacific-Basin Finance Journal, Elsevier, vol. 49(C), pages 1-14.
    4. Jørgen Vitting Andersen & Ioannis Vrontos & Petros Dellaportas & Serge Galam, 2014. "Communication impacting financial markets," Post-Print hal-01215750, HAL.
    5. Brad M. Barber & Terrance Odean & Ning Zhu, 2009. "Do Retail Trades Move Markets?," The Review of Financial Studies, Society for Financial Studies, vol. 22(1), pages 151-186, January.
    6. Chun-An Li & Chih-Cheng Yeh, 2011. "Investor Psychological and Behavioral Bias: Do High Sentiment and Momentum Exist in the China Stock Market?," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 14(03), pages 429-448.
    7. 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.
    8. 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.
    9. 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.
    10. Urquhart, Andrew, 2018. "What causes the attention of Bitcoin?," Economics Letters, Elsevier, vol. 166(C), pages 40-44.
    11. Malcolm Baker & Jeffrey Wurgler, 2007. "Investor Sentiment in the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 129-152, Spring.
    12. Siganos, Antonios & Vagenas-Nanos, Evangelos & Verwijmeren, Patrick, 2014. "Facebook's daily sentiment and international stock markets," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 730-743.
    13. Bin Gao & Chunpeng Yang, 2018. "Investor Trading Behavior and Sentiment in Futures Markets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(3), pages 707-720, February.
    14. 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.
    15. Aboody, David & Even-Tov, Omri & Lehavy, Reuven & Trueman, Brett, 2018. "Overnight Returns and Firm-Specific Investor Sentiment," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(2), pages 485-505, April.
    16. Thomas Dimpfl & Stephan Jank, 2016. "Can Internet Search Queries Help to Predict Stock Market Volatility?," European Financial Management, European Financial Management Association, vol. 22(2), pages 171-192, March.
    17. Timm O. Sprenger & Andranik Tumasjan & Philipp G. Sandner & Isabell M. Welpe, 2014. "Tweets and Trades: the Information Content of Stock Microblogs," European Financial Management, European Financial Management Association, vol. 20(5), pages 926-957, November.
    18. Shen, Dehua & Urquhart, Andrew & Wang, Pengfei, 2019. "Does twitter predict Bitcoin?," Economics Letters, Elsevier, vol. 174(C), pages 118-122.
    19. Zhang, Yongjie & Song, Weixin & Shen, Dehua & Zhang, Wei, 2016. "Market reaction to internet news: Information diffusion and price pressure," Economic Modelling, Elsevier, vol. 56(C), pages 43-49.
    20. Doojin Ryu & Hyeyoen Kim & Heejin Yang, 2017. "Investor sentiment, trading behavior and stock returns," Applied Economics Letters, Taylor & Francis Journals, vol. 24(12), pages 826-830, July.
    21. Xiong, Xiong & Meng, Yongqiang & Li, Xiao & Shen, Dehua, 2020. "Can overnight return really serve as a proxy for firm-specific investor sentiment? Cross-country evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 64(C).
    22. Alexander Hillert & Heiko Jacobs & Sebastian Müller, 2014. "Media Makes Momentum," The Review of Financial Studies, Society for Financial Studies, vol. 27(12), pages 3467-3501.
    23. repec:bla:jfinan:v:59:y:2004:i:3:p:1259-1294 is not listed on IDEAS
    24. Ni, Zhong-Xin & Wang, Da-Zhong & Xue, Wen-Jun, 2015. "Investor sentiment and its nonlinear effect on stock returns—New evidence from the Chinese stock market based on panel quantile regression model," Economic Modelling, Elsevier, vol. 50(C), pages 266-274.
    25. Kim, Soon-Ho & Kim, Dongcheol, 2014. "Investor sentiment from internet message postings and the predictability of stock returns," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 708-729.
    26. 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.
    27. David H. Solomon, 2012. "Selective Publicity and Stock Prices," Journal of Finance, American Finance Association, vol. 67(2), pages 599-638, April.
    28. 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.
    29. Alok Kumar & Charles M.C. Lee, 2006. "Retail Investor Sentiment and Return Comovements," Journal of Finance, American Finance Association, vol. 61(5), pages 2451-2486, October.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    socio-finance; sentiments; complex systems;
    All these keywords.

    JEL classification:

    • G4 - Financial Economics - - Behavioral Finance
    • G40 - Financial Economics - - Behavioral Finance - - - General

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    This paper has been announced in the following NEP Reports:

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