基于贝叶斯学习的最优互联网化房地产金融合约  

Optimal Internet-based Real Estate Financial Contract Based on Bayesian Learning

作　　者：郑军 胡蓉 ZHENG Jun;HU Rong(School of Finance,Guangdong University of Finance & Economics,Guangzhou 510320,China;School of Financial Mathematics and Statistics,Guangdong University of Finance,Guangzhou 510520,China)

机构地区：[1]广东财经大学金融学院,广东广州510320 [2]广东金融学院金融数学与统计学院,广东广州510520

出　　处：《运筹与管理》2019年第8期116-125,共10页Operations Research and Management Science

基　　金：广东省哲学社会科学规划项目“互联网化房地产金融契约经济激励效率及其风险研究”(GD15YYJ06);广东省教育厅科研项目“基于动态机制设计理论的房地产金融互联网科技化创新研究”(2015WQNCX044)

摘　　要：房地产金融的互联网化是当前金融市场创新的重要方向。本文采用动态道德风险理论研究了互联网化房地产金融合约的最优性及其经济特征,并以动态合约的视角考虑了参与方的贝叶斯学习对互联网化房地产金融最优性的影响。研究发现,为了激励资信良好的融资方努力工作且排除资信欠佳的融资方,互联网化房地产金融合约不仅需权衡激励成本和收益以确定适当的努力激励强度,而且还需考虑因融资方的信息优势带来的信息租金。The development of Internet finance innovation in real estate finance is an important direction for the current financial market innovation. This paper uses dynamic moral hazard theory to study the optimality and economic characteristics of Internet real estate financial contracts. At the same time, considering the dynamic characteristics of contracts, the article considers the influence of participants’ Bayesian learning on the optimality of Internet real estate finance. It is found that, in order to encourage good credit financiers to work hard while excluding bad credit financiers, Internet real estate financial contracts need tonot only tradeoff the incentive costs and benefits to choose the appropriate incentive intensity, but also consider the information rent brought by the information advantages of the financiers.

关 键 词：贝叶斯学习 动态道德风险 房地产金融 互联网金融 

分 类 号：F832.5[经济管理—金融学]