在线网络借贷投资决策模型及实证研究

发布时间：2018-06-26 00:34

  本文选题：网络借贷 + 投资决策　； 参考：《运筹与管理》2016年02期

【摘要】：P2P网络借贷作为电子商务在金融领域的延伸与应用,近年来得到广大学者的关注.但是目前的理论研究中,鲜有从投资者信息挖掘的角度进行投资决策分析.本文提出一个新颖的方法,即投资者构成分析方法,通过分析贷款的众多投资者信息遴选出最有价值的投资,辅助投资者进行投资决策.首先从投资者的历史投资收益率、风险偏好以及投资经验三个维度构建投资者档案(investor profile),进而基于投资者档案构建投资者构成分析模型,最后通过美国最大的在线网络借贷网站Prosper的数据,对本文提出的构想及模型进行了实证研究.实验结果表明本文提出的利用投资者构成分析的方法辅助投资者进行投资决策是可行的,文中构建的模型表现出良好的预测能力,能够有效地筛选出有价值的投资.
[Abstract]:P2P network lending, as an extension and application of e-commerce in the financial field, has attracted the attention of many scholars in recent years. However, in the current theoretical research, there is rarely an investment decision analysis from the perspective of investor information mining. In this paper, a new method is proposed, that is, the analysis method of the investor, through the analysis of the numerous investment of the loan. It selects the most valuable investment and assists investors to make investment decisions. First, we build investor files (investor profile) from the three dimensions of investors' return on historical investment, risk preference and investment experience, and then build an investor analysis model based on investor archives, and finally through the largest online network in the United States. The data of Prosper, an empirical study on the concept and model proposed in this paper, shows that the method proposed in this paper is feasible to assist investors in making investment decisions, and the model constructed in this paper shows good forecasting ability and can effectively screen out valuable investment.
【作者单位】： 大连理工大学管理与经济学部;
【基金】：国家自然科学基金资助项目(71402014) 教育部人文社科基金资助项目(14YJCZH044)
【分类号】：F713.36;F831.2
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本文编号：2068235