Finfluencers

Ali Kakhbod, Seyed Mohammad Kazempour, Dmitry Livdan and Norman Schuerhoff
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Ali Kakhbod: University of California, Berkeley
Seyed Mohammad Kazempour: Rice University-Jesse H. Jones Graduate School of Business

No 23-30, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: Tweet-level data from a social media platform reveals low average accuracy and high dispersion in the quality of advice by financial influencers, or ``finfluencers": 28% of finfluencers are skilled generating 2.6% monthly abnormal returns, 16% are unskilled, and 56% have negative skill (``antiskill'') generating -2.3% monthly abnormal returns. Consistent with homophily shaping finfluencers' social networks, antiskilled have more followers and more influence on retail trading than skilled finfluencers. The advice by antiskilled finfluencers creates overly optimistic beliefs most times and persistent swings in followers' belief bias. Consequently, finfluencers cause excessive trading and inefficient prices such that a contrarian strategy yields 1.2% monthly out-of-sample performance.

Pages: 55 pages
Date: 2023-03
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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp2330

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