A decision tree model for herd behavior and empirical evidence from the online P2P lending market

摘要

Herd behavior has been studied in a wide range of areas, such as fashion, online purchasing, and stock trading. However, to date, little attention has been paid to the herd behavior in online Peer-to-Peer lending market. With a decision tree, we model the formation of herding when decision makers with heterogeneous preferences are facing costly information acquiring and analyzing. Data from Prosper.com provides us with a good opportunity to explore empirical evidences for herd behavior. When herd behavior arises, individuals follow the behaviors of other people and generally ignore their own information which might cost them too much to obtain or analyze. Following this idea, we propose to detect herd behavior by focusing on investors' decision-making time variation. We observed that friend bids and bid counts impose significant effects on the decision-making time of investors, which is considered as the evidence of herding. We also conduct empirical analyses to address the impact of herd behavior on an individual's benefit. We reveal that lenders are more likely to herd on listings with more bids and friend bid, but their benefit will be reduced as the consequence of the behavior.