Symmetry | |
Accessing Information Asymmetry in Peer-to-Peer Lending by Default Prediction from Investors’ Perspective | |
Bo Yu1  Xinyuan Wei1  Yao Liu2  | |
[1] School of Mathematical Sciences, Dalian University of Technology, Dalian 116024, China;Simon Business School, University of Rochester, Rochester, NY 14627, USA; | |
关键词: default prediction; information asymmetry; L1/2-regularization; weighted logistic regression; peer-to-peer lending; | |
DOI : 10.3390/sym12060935 | |
来源: DOAJ |
【 摘 要 】
Recent a few years have witnessed the rapid expansion of the peer-to-peer lending marketplace. As a new field of investment and a novel channel of financing, it has drawn extensive attention throughout the world. Many investors have shown great enthusiasm for this field. However, investors are at the disadvantage of information asymmetry, which is a key issue in this marketplace that is unavoidable and can lead to moral hazard or adverse selection. In this paper, we propose an
【 授权许可】
Unknown