P2P网络借贷投资者的信息识别与行为偏差

发布时间：2018-04-03 14:01

本文选题：互联网金融　切入点：P2P网络借贷　出处：《清华大学》2014年博士论文

【摘要】：我国P2P网络借贷行业的发展呈现出爆发式的增长态势,受到了来自全球各地专家学者以及业内人士的关注。数据显示,截至2014年6月,我国的P2P网络借贷平台数量已经达到714家,预计到2014年底P2P网贷行业的全年累计成交额将有可能超过3000亿元。P2P网贷平台已经成为了中国民间金融中的重要借贷渠道。但目前我国缺乏完善的信用评分体系及个人信用数据的积累,使得网贷平台上的借款人披露的信息未必充分有效,这使得个体投资者处于信息劣势,那么投资者在这样的借贷环境下是否具有信息识别能力?投资者是否能够通过信息识别从而对订单的风险水平进行识别并做出有效判断?那些经验和知识明显不足的投资者如何进行信息识别?投资者对信息的识别是否完全?这些问题都有待探索。本文利用我国人人贷P2P网络借贷平台的交易数据对投资者信息识别问题进行了深入的实证研究,得出了以下三个主要结论:第一,尽管我国缺乏完善的个人信用评分体系、借款人披露的个人信息未必充分有效,使得P2P网贷平台的利率定价机制不完全,借款利率未必能反应借款人风险,但是即使在如此严重不对称的信息环境下,我们通过实证研究发现投资者仍然能够根据借款人披露的个人信息和订单信息,对借款人披露信息的价值进行识别,说明这些投资者具有一定程度的风险识别能力。这为我国P2P网贷行业的发展提供了一定的基础。第二,本文进一步研究了投资者能否通过观察他人投资行为进行信息识别的问题。研究发现:人人贷平台上投资者行为存在明显的羊群效应,且这种羊群效应背后有明显的信息传递证据。第三,在前两部分的基础上,本文继续检验了投资者对信息识别是否完全的问题。本文试图通过寻找投资者行为偏差的方式来证实投资者信息识别不完全性,结果发现投资者进行信息识别的时候存在明显的地域歧视,该结果说明投资者的信息识别程度是不完全的。本论文的研究为理解信息不对称情况下个体投资者的信息识别提供了新的视角;同时对于理解利率市场化、投资者行为等相关话题也具有一定的理论和现实意义。
[Abstract]:The development of P2P network lending industry in China shows a explosive growth trend, which has attracted the attention of experts and scholars from all over the world as well as the industry.Data show that as of June 2014, the number of P2P network lending platforms in China has reached 714.It is expected that by the end of 2014, the total annual turnover of P2P loan industry will probably exceed 300 billion yuan. P2P lending platform has become an important lending channel in Chinese private finance.However, the lack of a perfect credit scoring system and the accumulation of personal credit data in our country make the information disclosed by borrowers on the Internet loan platform not fully effective, which makes individual investors in the information disadvantage.Do investors have the ability to identify information in such a lending environment?Can investors identify the risk level of an order by identifying the information and make an effective judgment?How do those investors with a clear lack of experience and knowledge carry out information identification?Is the investor's recognition of the information complete?These questions need to be explored.Based on the transaction data of peer-to-peer lending online lending platform in China, this paper makes an in-depth empirical study on the identification of investors' information, and draws the following three main conclusions: first, despite the lack of a perfect personal credit scoring system in China,The personal information disclosed by the borrower may not be sufficiently effective, which makes the interest rate pricing mechanism of P2P network and lending platform incomplete, and the borrowing rate may not reflect the borrower's risk, but even in such a severely asymmetric information environment,Through empirical research, we find that investors can still identify the value of information disclosed by borrowers according to the personal information and order information disclosed by borrowers, indicating that these investors have a certain degree of risk identification ability.This provides a certain basis for the development of P2P network loan industry in China.Secondly, this paper further studies whether investors can identify information by observing the investment behavior of others.It is found that the herding behavior of investors on peer-to-peer lending platform has obvious herding effect, and there is obvious evidence of information transmission behind this herding effect.Thirdly, on the basis of the first two parts, this paper continues to examine whether investors' information recognition is complete.This paper tries to prove the incompleteness of investor information identification by looking for the way of investor behavior deviation. The result shows that there is obvious regional discrimination when investors identify information.The results show that the degree of information recognition of investors is incomplete.The research in this paper provides a new perspective for understanding the information identification of individual investors under the condition of asymmetric information. At the same time, it has certain theoretical and practical significance for understanding the interest rate marketization, investor behavior and other related topics.
【学位授予单位】：清华大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：F724.6;F832.4

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