本文以2002-2017年我国A股周数据为样本, 首先计算了76个细分行业的股指波动率, 并在此基础上通过高维时变参数向量自回归(HD-TVP-VAR)模型构建了行业之间的全局风险网络. 进一步地, 本文从网络拓扑分析与量化实证分析两个角度考察了金融行业在风险网络中的系统重要性. 研究发现, 1) 我国A股市场各行业间的风险溢出呈现出"唇齿相依"的复杂关联结构, 且风险事件的爆发与金融行业对实体经济行业风险溢出的变化密切相关; 2) 金融行业承担着风险吸收的功能, 其中, 银行业的风险吸收功能最强, 而证券期货业则表现出相对更明显的风险扩散性; 3) 行业关联性增强、行业风险角色向扩散型转化以及风险网络结构均衡性受破坏是系统性金融风险产生的重要根源; 4) 金融行业在全局风险网络中的系统重要性显著强于实体经济行业, 其中, 银行业与证券期货业的系统重要性分居首位与次位; 5) 房地产行业在全局风险网络中发挥着双向风险放大的风险"桥梁"作用; 6) 高杠杆与高流动性会显著刺激金融行业风险扩散的系统重要性, 而大规模与重投资则会显著增强其风险吸收的系统重要性.
Abstract
Employing a weekly sample of Chinese A shares from 2002 to 2017, this paper first computes the sector volatility index for 76 sub-sectors. Based on these indices, a global risk network among sectors is then constructed through a high-dimensional time-varying parameters vector autoregressions (HD-TVP-VAR) model. Afterwards, this paper further examines the systemic importance of financial industries in the risk network from both network topology and empirical analysis perspectives. Results show that, risk spillovers among sectors in Chinese stock market exhibit a complex network structure featured with high connectedness. Specifically, the outbreak of risk events is closely related to the changes in spillover connectedness from financial industries to real economy industries. Second, financial industries play an important role of absorbing risk, with banking being the major risk taker, while the security and future sector being the major risk spreader. Third, the increase in connectedness, transferring from risk-taker to risk-spreader, and the destruction to the stability of network equilibrium are main driving forces underlying systemic financial risk. Forth, financial industries have a greater systematic importance than real economy industries, within which, banking ranks on the top, followed by the security and future sectors. Fifth, real estate sector serves as a risk "bridge" between financial industries and real economy industries which magnifies risk from both sides. Last, high leverage and high liquidity will stimulate risk diffusion, but large scale and heavy investment will help to strengthen risk absorption.
关键词
系统重要性 /
系统性金融风险 /
HD-TVP-VAR模型 /
复杂网络
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Key words
systemic importance /
systemic financial risk /
HD-TVP-VAR model /
complex network
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中图分类号：
F832
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基金
广东省自然科学基金面上项目(2016A030313094, 2019A1515012018); 广东省软科学研究领域(2019A101002015)
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