|本期目录/Table of Contents|

[1]吴小英,鞠 颖*.基于最小二乘法的网络借贷模型[J].厦门大学学报(自然科学版),2012,51(6):980.
 WU Xiao-ying,JU Ying*.Online Lending Model Based on Ordinary Least Square[J].Journal of Xiamen University(Natural Science),2012,51(6):980.
点击复制

基于最小二乘法的网络借贷模型(PDF)
分享到:

《厦门大学学报(自然科学版)》[ISSN:0438-0479/CN:35-1070/N]

卷:
51卷
期数:
2012年第6期
页码:
980
栏目:
研究论文
出版日期:
2012-11-30

文章信息/Info

Title:
Online Lending Model Based on Ordinary Least Square
作者:
吴小英鞠 颖*
厦门大学信息科学与技术学院,福建 厦门 361005
Author(s):
WU Xiao-yingJU Ying*
School of Information Science and Technology,Xiamen University,Xiamen 361005,China
关键词:
P2P借贷 借款用途 借款成功率
Keywords:
P2P lending lending purpose successful fund rate
分类号:
R 319
文献标志码:
A
摘要:
网络借贷是近年来出现的新兴事物,研究网络借贷中借款用途对借贷成功率的影响.通过使用美国最大的P2P网络借贷Prosper网站2007年以来的数据,以单一变量原则建立数学模型,并使用最小二乘法进行参数估计,回归实证研究表明:同等条件下,学生借款比其他种借款成功率低3.4%,分析其原因发现学生还款率并不比其他的低,因此对学生存在直觉歧视.通过类似的方法,还发现用于汽车或者其他方面的债务更容易借到钱.同时,实证研究还得出了其他若干因素,如借款金额、利率等对借款成功率的影响.
Abstract:
P2P online lending is an emerging economic lending model.In this work we study the influence of the purpose of lending on success rate at online lending marketplace.Using the data of American largest P2P lending market Prosper since 2007,we establish mathematical model,and employ ordinary least square,univariate multiple regression.The experimental results show that,the successful rate of student loan is 3.4% lower than the others,ceteris paribus.The reason is not due to low student repayment,but because of taste-based discrimination.On the other hand,for auto loan or other loan,it is easier to get fund successfully.Meanwhile,we also investigate the influence of other factors,such as loan amount and rate.

参考文献/References:

[1] 莫易娴.P2P网络借贷国内外理论与实践研究文献综述[J].金融理论与实践,2011(12):101-104.
[2] 王继晖,李成.网络借贷模式下洗钱风险分析及应对[J].金融与经济,2011(9):9-11.
[3] 陈盛东.依法管贷后记:借款用途莫虚设[J].中国农村信用合作,2001(1):32-33.
[4] 邢增艺,王艳.网络借贷:微型金融发展新趋势[J].前沿,2010(23):109-111.
[5] 王艳,陈小辉,邢增艺.网络借贷中的监管空白及完善[J].当代经济,2009(24):46-47.
[6] Prosper Company.Prosper marketplace[EB/OL][2012-09-10].http://www.prosper.com.
[7] Berger S,Gleisner F.Emergence of financial intermediaries in electronic markets:the case of online P2P lending[J].Business Research,2009,2(1):39-65.
[8] Krumme K,Herrero-lopez S.Do lenders make optimal decisions in a peer-to-peer network?[C]//Web Intelligence and Intelligent Agent Technologies.Milan,Italy:IEEE,2009:124-127.
[9] Lauri P,Teich J E,Wallenius H,et al.Borrower decision aid for people-to-people lending[J].Decis Support Syst,2010,49(1):52-60.
[10] Luo C,Xiong H,Zhou W,et al.Enhancing investment decisions in P2P lending:an investor composition perspective[C]//Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.New York,USA:ACM,2011:292-300.
[11] Barasinska N,Schäfer D.Are women more credit-constrained than men-evidence from a rising credit market[C]//Advisory and Steering Committee Meeting.Berlin,Germany:FINESS,2010:1-27.
[12] Hampshire S R,Krishnan R.Asearch theoretic model of person-to-person lending[EB/OL][2012-09-10].http://heinz.cmu.edu/research/244full.pdf.
[13] 刘严.多元线性回归的数学模型[J].沈阳工程学院学报:自然科学版,2005,1(增刊1):128-129.
[14] Li Siming,Qiu Jiaxian,Lin Zhangxi,et al.Do borrowers make homogeneous decisions in online P2P lending market?an empirical study of PPDai in China[C]//2011 8th International Conference on ICSSSM.Tianjin,China:IEEE,2011:1-6.
[15] Becker G S.The economics of discrimination[M].Chicago:University of Chicago Press,1971.

备注/Memo

备注/Memo:
收稿日期:2012-03-06
*通信作者:yju@xmu.edu.cn
更新日期/Last Update: 2012-11-20