创业投资网络风险传染机制及效应研究

At present, China's venture capital industry is in a period of deep retreat after rapid development, and market opportunities and investment risks coexist. “It is difficult to raise funds, investment is difficult, and exit is difficult” has become an industry problem, but the risks behind it have not received enough attention. The network structure is the key to determining the risk contagion effect, and it is also the key to the evolution of individual risk to systemic risk. This project starts with the risk identification of the venture capital network and carries out the research on the mechanism and effect of risk contagion. First, the project identifies the financing, decision-making, linkage, and exit risks that an organization may encounter in a network for the operational processes and network specificity of a venture capital institution. Secondly, the stochastic differential equation is used to establish the risk infection model of venture capital network, and the theoretical mechanism of risk contagion including risk dependence, risk transfer and risk acceleration factor is established. Thirdly, based on big data simulation, the cyber risk contagion effect between venture capital institutions, venture capital institutions and start-ups, and venture capital institutions' geographic populations is explored, and the factors affecting network risk contagion are explored. Next, through the use of the associated risk panel data of 1737 venture capital institutions, an empirical test on the risk contagion effect of venture capital networks is conducted. Finally, a risk early warning model is constructed, and a risk-infected immunization strategy for venture capital networks is proposed.

当前，我国创业投资行业处于高速发展后的深度回调时期，市场机会与投资风险并存。“募资难、投资难、退出难”成为行业难题，其背后蕴含的风险却仍未得到足够重视。网络结构是决定风险传染效应的关键，也是个体风险演变升级为系统性风险的关键。本项目从创业投资网络的风险识别入手，展开风险传染的机制和效应研究。首先，本项目针对创业投资机构的运作流程和网络特殊性，识别机构在网络中可能遇到的募资、决策、关联和退出风险。其次，采用随机微分方程建立创业投资网络风险传染模型，确立包含风险依赖、风险传递和风险加速因子的风险传染理论机制。再次，基于大数据仿真模拟测算分别针对创投机构间、创投机构与初创企业间、创投机构地理族群间的网络风险传染效应，探求网络风险传染影响因素。接下来，通过采用1737家创业投资机构的关联风险面板数据，对创业投资网络风险传染效应进行实证检验。最后，构建风险预警模型，提出创业投资网络风险传染免疫策略。

当前，我国创业投资行业处于深度回调后的复苏时期，市场机会与投资风险并存。在科创板试点注册制4年后，我国全面实行股票发行注册制，旗帜鲜明地引导资本要素支持科技创新企业，进一步打通“募、投、管、退”环节。上市企业扩容的机遇与新股破发的风险并存，是对创业投资机构的网络赋能能力和风险管控体系的一次重要挑战。本项目遵循“创投网络测度——风险效应检验——免疫策略构建”的分析脉络，研究了我国创业投资网络的形成、作用、风险成因及风险传染与免疫策略。首先，基于社会网络理论和复杂网络研究方法，测度了我国创业投资网络的动态演进过程，发现虽然创业投资网络整体呈扩张化、复杂化，但网络质量并没有提升。其次，基于创业投资机构“募、投、管、退”运作流程，从政策冲击下强监管信号对创业投资机构募资的长短期影响、创业投资决策的趋同效应和风险致因体系构建、股价崩盘风险和业绩下滑风险对创业投资机构关联上市公司的影响、新形势下创业投资机构退出失败案例研究等方面，进行了事前事中事后的全过程风险评估、主要效应测度和重要后果评价。最后，从网络构建、外部环境优化、内部要素提升等多方面提出了我国创业投资网络风险传染免疫策略。本项目拓展了创业投资网络“传染”问题的研究范畴，对加强资本市场监管和防范金融风险传染提供了新思路，为促进我国创业投资行业的持续健康发展提供了具有前瞻性和可操作性的建议。