宏观基本面中的稀疏成分与股市波动率  

Sparse Components in Macroeconomic Fundamentals and Stock Market Volatility

作　　者：金霜 李正阳 金鹏瑞 JIN Shuang;LI Zheng-yang;JIN Peng-rui(School of Business and Economics,University Putra Malaysia,Negeri Selangor 43400,Malaysia;Ningxia Credit Reporting Co.,Ltd.,Yinchuan 750000,China;University of Birmingham,Birmingham B15,UK)

机构地区：[1]马来西亚博特拉大学经济管理学院,马来西亚雪兰莪州43400 [2]宁夏征信有限公司,宁夏银川750000 [3]英国伯明翰大学,英国伯明翰B15

出　　处：《山西财经大学学报》2024年第S02期65-67,共3页Journal of Shanxi University of Finance and Economics

摘　　要：利用滚动窗口法和规则化回归方法,深入分析中国宏观经济基础与股市震荡之间的关系,以及相关因素对股价波动的影响机制。研究表明:稀疏特征在波动性预测中的效果略优于稀疏因子,但过多地使用会导致误差增大;影响股市波动的因素并非仅限于基本面信息;不同类型的特征和因子对于波动率的预测有着各自独特的规律。在对市场特征进行预测时,市盈率和住房销售增长率具备显著的影响,而在因子预测中,波动率的自回归项目作为补充起着关键作用。Utilizing the scrolling window method and regularized regression techniques,this paper conducted an in-depth analysis of the relationship between China’s macroeconomic fundamentals and stock market volatility,as well as the influencing mechanism of relevant factors on stock price fluctuations.The research findings indicated that sparse features exhibited slightly better performance than sparse factors in volatility forecasting,but excessive use could lead to increased errors.Factors influencing stock market volatility extended beyond mere fundamental information.Different types of features and factors had their own unique patterns when predicting volatility rated.In market characteristic prediction,the price-to-earnings ratio and housing sales growth rate exerted significant impacts,whereas in factor prediction,the auto-regressive item of volatility served as a crucial supplement.

关 键 词：宏观基本面 稀疏成分 股市波动率预测 滚动窗口 规则化回归 

分 类 号：F832.51[经济管理—金融学] F124