摘要
利用高维分位数因子模型提取个股分位数变化的共同成分以衡量尾部系统风险,采用正则化回归分析尾部系统风险的宏观来源,通过截面回归探讨企业特质对尾部系统风险受宏观风险因子影响差异的作用。研究表明,中国股市尾部系统风险具有较强的高低位不对称性,高位尾部风险更多地与市场不确定性增大相联系,具有更强波动性且受宏观风险因素影响复杂度更高。尾部系统风险的不对称性随极端条件的加剧增强。企业特征能够对尾部系统风险受宏观风险因素影响的差异进行解释,企业规模、资产负债率及可持续增长率是影响这一差异性的重要因素。
This paper extracts common components in quantiles of stock market,returns using a highdimensional factor model to evaluate the tail systematic risk.It.investigates the macro sources of the tail systematic risk by using regularized regressions and explores the effects of firm characteristics on the heterogeneity of the sensitivity of the tail systematic risk to macro risk factors via cross sectional regressions.The results show that,the upside and downside tail systematic risks are asymmetric.The upside risk is more related to the increase in market,uncertainty,has a higher volatility and a more complex relation with macro risk factors compared to downside risk.The asymmetry becomes more significant,when the quantiles move to tails.Firm characteristics do have an explanatory power on the heterogeneity of the sensitivity of the tail systematic risk to macro risk factors,with the firm size,the debt,asset,ratio,and the self-sustainable growth rate being the most,influential characteristics.
作者
李伯龙
LI Bolong(School of Finance,Nankai University,Tianjin 300350,China)
出处
《系统管理学报》
CSSCI
CSCD
北大核心
2021年第6期1079-1087,共9页
Journal of Systems & Management
基金
国家留学基金资助项目(201906200008)。
作者简介
李伯龙(1991-),男,博士生。研究方向为金融计量。E-mail:libolong2014@outlook.com。
