本文選題：P2P網(wǎng)絡借貸 + 公開信息�。� 參考：《華僑大學》2017年碩士論文

【摘要】：業(yè)內(nèi)將2013年稱為互聯(lián)網(wǎng)金融元年,這一年在互聯(lián)網(wǎng)快車的帶動下,金融行業(yè)迅速衍生出了一系列創(chuàng)新活動。2007年6月,國內(nèi)第一家P2P網(wǎng)絡借貸平臺“拍拍貸”成功創(chuàng)立,緊接著與之具有同樣業(yè)務形態(tài)的紅嶺創(chuàng)投、人人貸等平臺也先后出現(xiàn),P2P網(wǎng)絡借貸作為一種新的融資渠道正在蓬勃發(fā)展�；I資人在平臺借款時要提供個人信息等相關(guān)資料,這些信息會在借款標的頁面公開顯示。由于金融市場中信息不對稱普遍存在,P2P網(wǎng)絡借貸平臺發(fā)揮的雖是金融中介作用,但多數(shù)只是對籌資人提供的材料進行審核,因此籌資人為了提高借款成功率可能會隱瞞自身情況或提供虛假信息,投資人在選擇借款標的時需要對公開信息的真實性進行甄別。本文使用Probit模型,在模型中加入了籌資人的網(wǎng)絡聲譽、工作狀況和借款描述變量,并創(chuàng)新性的使用句讀對借款描述的文本可讀性進行量化,以人人貸平臺數(shù)據(jù)為基礎(chǔ),研究公開信息對P2P網(wǎng)絡借貸行為(包括借款成功和還款違約)的影響,并通過對比兩者的影響因素,觀察是否存在信息噪音,即對投資人而言具一定欺騙性的信息,從而幫助投資者進行信息甄別。研究結(jié)果顯示:(1)籌資人的網(wǎng)絡聲譽影響借款成功率,且能夠客觀反映其違約風險,為投資人提供較為準確的參考信息�；I資人的借款還清率越高、逾期次數(shù)越少,表明其違約風險越低,因而較受投資人的青睞,借款成功率較高。(2)籌資人所提供的工作狀況等個人信息影響借款成功率,但在揭示還款違約方面存在信息噪音。對于一些難以認證的個人信息(如公司規(guī)模、收入),籌資人可能存在虛假披露情況,此類信息將會對投資人造成干擾,使其不能準確判斷籌資人的違約風險。(3)借款描述影響借款成功率,但在揭示籌資人違約風險方面存在信息噪音。借款描述的字數(shù)越多、文本可讀性越強,則借款成功率越高。但財務狀況或誠信水平較差的籌資人可能會借此進行偽裝,提供虛假的借款描述來欺騙投資人。
[Abstract]:The industry called 2013 the first year of Internet finance, led by the Internet Express, quickly spawned a series of innovative activities. In June 2007, PPDAI, the country's first P2P online lending platform, was founded successfully. Then with the same business form of Hongling Venture, people loan and other platforms have emerged P2P network lending as a new financing channel is booming. The fundraiser should provide personal information and other relevant information when borrowing on the platform, which will be publicly displayed on the loan subject page. Because of the widespread information asymmetry in financial markets, P2P network lending platforms play a financial intermediary role, but most of them only audit the materials provided by the financiers. Therefore, in order to improve the success rate of borrowing, the financier may conceal his own information or provide false information, and investors should identify the authenticity of the public information when selecting the subject matter of the loan. This paper uses Probit model to add the network reputation, work condition and loan description variables of the fundraiser, and innovatively uses sentence reading to quantify the readability of the loan description, which is based on the data of everyone's loan platform. This paper studies the influence of public information on P2P network borrowing behavior (including loan success and repayment default), and by comparing the two factors, we observe whether there is information noise, that is, information that is deceptive to investors. To help investors identify information. The research results show that the network reputation of the fundraiser affects the success rate of borrowing, and can objectively reflect the default risk, and provide more accurate reference information for investors. The higher the repayment rate and the less overdue, the lower the risk of default, and therefore more favored by investors. The higher the success rate of borrowing is, the higher the personal information such as the working condition provided by the financier affects the success rate of borrowing. But there is information noise in revealing default payments. For personal information that is difficult to authenticate (such as the size of the company, the revenue, the potential for false disclosure on the part of the financier, such information will interfere with investors, Therefore, it can not accurately judge the default risk of the financier. 3) the loan description affects the loan success rate, but there is information noise in revealing the default risk of the financier. The more words the loan describes and the more readable the text, the higher the success rate. But financiers with poor financial standing or integrity may use it to disguise themselves by providing false loan descriptions to deceive investors.
【學位授予單位】：華僑大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：F724.6;F832.4

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本文編號：1978309