| In recent years, P2 P online lending has grown rapidly both at China and abroad. Through the fast and easy network interfaces, P2 P has helped a lot of demanders who can not obtain funds from traditional channels, and also enables the investors to profit. The purpose of this paper is to study both parties involved on the platform, and trying to explore the behavior rules of borrowers and lenders from both theoretical and empirical aspects.This paper studies both the debit and credit sides from P2 P online lending Platform. We sorts out and explain the behavior rules of borrowers and lenders by using the theoretical research, theoretical models and empirical research method. Based on the review and comments on P2 P online lending of both domestic and foreign, we explore the behavior rules of borrowers and lenders by using asymmetric information theory, social capital theory and behavioral finance theory. Based on the model of informational cascades, we make some improvement and extension and establish a Bayesian-based informational cascades model for P2 P online lending. Based on this model, this article theoretically discusses the herd effect which may happen within lenders and the influence of each model parameters on the herd. Then, we get the transaction data of PPdai platform through software. By building a Logistic model, we study the factors which affect the full funding of a list, and we also built a predicting models for borrowers. In the fourth chapter,we demonstrates the loans lenders are herding on the platform by using subsequent tendering method.The main conclusions are as follow: asymmetry information theory, social capital theory and behavioral finance theory can be used to interpret the behavior of both debit and credit sides of P2 P online lending, and the informational cascades model theoretically illustrates that the herd effect may be existent in the P2 P lending market. Cluster analysis reveals that borrowers’ activities and behavior patterns differ a lot and their features could not be fully represented by the ’credit ratings’ designed by PPDai. The results of factor analysis on full funding show that credit rating, interest rates and other factors have a significant impact on borrow lists,but loan term and times are not recommended to stay in the model. The empirical results also show that with the increase of the number of tender, the probability of subsequent tenders will increase. It means that herd behavior is existent in the P2 P lending market. |
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