摘要
近年来,随着股权众筹的迅速发展,其在实际运作中风险评估和防范问题引起了人们的关注。基于此,本文首先利用主成分分析的方法构建了股权众筹风险评估指标体系,其次,利用BP神经网络以众投邦平台股权众筹项目为例进行了实证研究。结果显示:众筹风险评估指标体系由审核估值风险、发起人能力风险、项目本身风险、法律风险、经营风险、监管风险及流动性风险等七个指标构成;BP神经网络的方法在股权众筹风险评估方面是可行且有效的。研究结论可为我国股权众筹风险评估和防控及金融风险防控具有重要的理论及现实意义。
In recent years,with the rapid development of equity crowdfunding,its risk assessment and prevention problems in practical operation have attracted people’s attention. Based on this,the risk assessment index system of equity crowdfunding is constructed by principal component analysis,and then,an empirical research is done by taking"Zhongtoubang"as an example by using BP neural network. Results show that the system of risk assessment of equity crowdfunding is composed of seven indicators,including audit and valuation risk,sponsor ability risk,project risk,legal risk,business risk,regulatory risk and liquidity risk. BP neural network method is feasible and effective in the risk assessment of equity crowdfunding. The research conclusion has important theoretical and practical significance for risk assessment,prevention and control level of equity crowdfunding and financial risk prevention and control in China.
作者
夏诗颖
孔昭君
丁宣宣
石晓阳
Xia Shiying;Kong Zhaojun;Ding Xuanxuan;Shi Xiaoyang(Sehool of Management and Economics,Beijing Institute of Technology,Beijing 100081,China)
出处
《技术经济》
CSSCI
北大核心
2021年第11期146-154,共9页
Journal of Technology Economics
基金
国家自然科学基金“开放式创新网络众包模式的运行机理及行为管理研究”(71572012)
北京市社会科学基金项目“基于创新驱动的小微企业股权众筹融资模式运行机理及风险监控研究”(15JDJGB022)。
关键词
股权众筹
主成分分析
BP神经网络
风险评估
equity crowdfunding
principal component analysis(PCA)
back propagation(BP)neural network
risk appraisal