运筹与管理 ›› 2019, Vol. 28 ›› Issue (8): 116-125.DOI: 10.12005/orms.2019.0182

• 应用研究 • 上一篇    下一篇

基于贝叶斯学习的最优互联网化房地产金融合约

郑军1, 胡蓉2   

  1. 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
  • 收稿日期:2018-09-06 出版日期:2019-08-25
  • 作者简介:郑军(1981-),男,贵州铜仁人,讲师,博士,研究方向:房地产金融,宏观金融;通讯作者:胡蓉(1979-),女,湖南衡阳人,讲师,博士,研究方向:金融计算,数据挖掘。
  • 基金资助:
    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)

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

ZHENG Jun1, HU Rong2   

  1. 1.School of Finance, Guangdong University of Finance & Economics, Guangzhou 510320, China;
    2.School of Financial Mathematics and Statistics, Guangdong University of Finance, Guangzhou 510520, China
  • Received:2018-09-06 Online:2019-08-25

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。

关键词: 贝叶斯学习, 动态道德风险, 房地产金融, 互联网金融

Abstract: 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.

Key words: bayesian learning, dynamic moral hazard, real estate finance, internet finance

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