中国股市流动性风险研究——基于金融市场微观结构视角  

On Liquidity Risk of Chinese Stock Market from Perspective of Financial Market Microstructure

作　　者：王文胜 刘倩 WANG Wen-sheng;LIU Qian(School of Economics,Hangzhou Dianzi University,Hangzhou Zhejiang 310018,China)

机构地区：[1]杭州电子科技大学经济学院,浙江杭州310018

出　　处：《杭州电子科技大学学报（社会科学版）》2020年第5期36-41,共6页Journal of Hangzhou Dianzi University：Social Sciences

基　　金：国家自然科学基金项目(11671115)。

摘　　要：金融市场中,风险的度量及预测一直都是被关注和研究的重点。文章通过构建价格极差-交易量-广义自回归条件异方差模型,对股票市场的流动性风险进行度量,并利用上证指数2011年1月4日至2019年4月30日2000多个数据作为样本进行实证检验。结果表明,改进后的模型不仅能改善模型的拟合预测效果,广义自回归条件异方差效应的解释能力明显减小,而且所有价格极差和交易量的系数估计量均为正,说明把交易量和价格极差作为代理变量来研究收益率的持续波动性具有一定的解释作用。同时改进模型比传统模型预测的风险值更加准确,错误率更低。In the financial market,risk measurement and prediction have always been the focus of attention and research.The paper measures the liquidity risk of the stock market by constructing a price range-transaction volume-generalized autoregressive conditional heteroscedastic model,and uses more than 2,000 data from the Shanghai Stock Index from January 4,2011 to April 30,2019 as samples for its empirical inspection.The results show that the improved model can not only improve the model s fitting prediction effect,the explanatory power of the generalized autoregressive conditional heteroskedasticity effect is significantly reduced,and all the price extremes and transaction volume coefficient estimates are positive,which indicates that the transaction volume and the price extremes are used as proxy variables to study the continuous volatility of the rate of return has some certain explanatory effects.Meanwhile the improved model has more accurate risk value and lower error rate than the traditional one.

关 键 词：流动风险 交易量 价格极差 广义自回归条件异方差模型 回测检验 

分 类 号：F832.5[经济管理—金融学]