Herding behaviour in P2P lending markets

Mustafa Caglayan, Oleksandr Talavera, Wei Zhang

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We explore lender behaviour on Renrendai.com, a leading Chinese peer-to-peer (P2P) crowdlending platform. Using a sample of around five million investor-loan-hour observations, and applying a high-dimensional fixed effect estimator, we confirm evidence of herding behaviour: the investors in our sample prefer assets that had attracted strong interest in previous periods. The herding behaviour relates to both the experience level of the investor and the length of time of an investment session on the platform. We also provide evidence of significant herding behaviour in the first hour of experienced investors’ sessions. Our results are robust to the use of alternative specifications.
Original languageEnglish
Pages (from-to)27-41
Number of pages15
JournalJournal of Empirical Finance
Early online date2 Jun 2021
Publication statusPublished - Sept 2021

Bibliographical note

Funding Information:
This work has been supported by the Economic and Social Research Council (ESRC), UK grant ES/P004741/1 . We thank Haofeng Xu and Linh Vi for their excellent research assistance, as well as the seminar participants at the National Bank of Ukraine and University of Reading and conference participants at FMARC 2019 and ECOMOD 2019 for their insightful comments and suggestions. We are particularly grateful to seminar participants at BOFIT, Zuzana Fungacova for their valuable feedback. Special thanks to Gregory Moore and Chloe Mitchel for editing the paper. The standard disclaimer applies.

Publisher Copyright:
© 2021 Elsevier B.V.


  • Crowdlending
  • FinTech
  • Herding
  • Investor experience
  • Peer-to-peer

ASJC Scopus subject areas

  • Finance
  • Economics and Econometrics


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