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浙江大学学报(理学版)  2023, Vol. 50 Issue (4): 434-441    DOI: 10.3785/j.issn.1008-9497.2023.04.007
数学与计算机科学     
基于VAR和EGARCH的投资者情绪对股市收益率的影响研究
高振斌1(),梁兴碧2
1.西安财经大学 统计学院,陕西 西安 710100
2.重庆移通学院 公共基础教育部,重庆 401420
Research on the impact of investor sentiment on stock market returns based on VAR and EGARCH
Zhenbin GAO1(),Xingbi LIANG2
1.School of Statistics,Xi'an University of Finance and Economics,Xi'an 710100,China
2.Ministry of Public Basic Teaching,Chongqing College of Mobile Communication,Chongqing 401420,China
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摘要:

借鉴国内外已有成果,用主成分分析法将2个主观指标与4个客观指标相结合,形成一个能有效衡量投资者情绪的综合指标,其能反映6个原始指标的大部分信息,且与股市收益率显著相关。在研究投资者情绪波动和股市收益率波动时,用向量自回归(vector autoregression,VAR)模型探索了二者间的关系;考虑证券市场信息的不对称性,运用了指数广义自回归条件异方差(exponential generalized autoregressive conditional heteroskedasticity,EGARCH)模型。研究表明,投资者消极悲观情绪对股市收益率的冲击作用大于积极乐观情绪;投资者情绪受收益率下降的冲击影响远大于收益率上涨的影响。

关键词: 投资者情绪向量自回归模型(VAR)指数广义自回归条件异方差(EGARCH)模型    
Abstract:

Based on the existing results at home and abroad, this paper uses principal component analysis to combine two subjective sentiment indicators and four objective sentiment indicators into a comprehensive index that can effectively measure investor sentiment. The constructed composite sentiment index can reflect most of the information of the six original indicators, and is significantly correlated with the stock market return rate. When studying the relationship between investment sentiment fluctuation and stock market return fluctuation, vector autoregression (VAR) model is used to explore the relationship between them. Accounting for asymmetry of stock market information, exponential generalized autoregressive conditional heteroskedasticity (EGARCH) model is used in this paper. The results show that the impact of negative and pessimistic sentiment on stock market returns is greater than that of positive and optimistic sentiment. The impact of falling earnings on investor sentiment is far greater than that of rising earnings.

Key words: investor sentiment    vector autoregression (VAR)    exponential generalized autoregressive conditional heteroskedasticity (EGARCH)
收稿日期: 2022-03-15 出版日期: 2023-07-17
CLC:  F 830.91  
作者简介: 高振斌(1966—),ORCID:https://orcid.org/0000-0002-0178-1975,男,博士,副教授,主要从事统计建模理论与应用研究,E-mail:zhenbingao@xaufe.edu.cn.
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引用本文:

高振斌, 梁兴碧. 基于VAR和EGARCH的投资者情绪对股市收益率的影响研究[J]. 浙江大学学报(理学版), 2023, 50(4): 434-441.

Zhenbin GAO, Xingbi LIANG. Research on the impact of investor sentiment on stock market returns based on VAR and EGARCH. Journal of Zhejiang University (Science Edition), 2023, 50(4): 434-441.

链接本文:

https://www.zjujournals.com/sci/CN/10.3785/j.issn.1008-9497.2023.04.007        https://www.zjujournals.com/sci/CN/Y2023/V50/I4/434

名称说明来源
消费者信心指数(CCI)每月的消费者信心指数中国经济社会大数据研究平台
投资者信心指数(ICI)每月的投资者信心指数中国证券公司
新增开户数(NA/万)每月累计成交量中经网统计数据库
换手率(TR/%)成交量/流通股本RESSET数据库
股票成交量(VOL/亿股)每月累计成交量RESSET数据库
市场市盈率(PE/%)加权平均计算的市盈率RESSET数据库
表1  月度指标的选取与说明
指标有效数据极小值极大值均值标准差偏度峰度
CCI10597.00126.60110.719.000.37-1.32
ICI10541.3071.2055.156.660.380.05
NA/万10514.27719.86163.63140.531.604.29
TR/%1057.2964.1219.2711.962.315.38
VOL/亿股1051 044.3612 854.434 000.322 567.771.803.21
PE/%10514.8440.2323.246.100.73-0.12
表2  代理指标描述性统计结果
指标

Pearson

相关性

滞后一期的指标

显著性

(双侧)

ICI0.482***ICI10.596***
CCI0.456***CCI10.459***
NA0.849***NA10.783***
TR0.753***TR10.671***
PE0.724***PE10.670***
VOL0.883***VOL10.882***
表3  相关性分析结果
图1  标准化后的FISI与SHR走势图
指标Pearson 相关性
FISISHP
FISH10.320**
SHP0.320**1
表4  FISI与SHR的相关性分析
图2  VAR模型稳定性检验结果
原假设滞后期数FP结论
SHR不是FISI的Granger原因42.953 30.024 1拒绝
FISI不是SHR的Granger原因41.527 10.200 8接受
表5  FISI与SHR的Granger因果检验
原假设滞后期数FP结论
SZR不是FISI的Granger原因42.934 80.024 8拒绝
FISI不是SZR的Granger原因40.408 20.802 3接受
表6  FISI与SZR的Granger因果检验
EGARCH模型系数结果
条件均值方程C-0.165 2***
C10.017 8**
C20.827 3***
条件方差方程ω-1.529 3***
α10.777 8***
η1-1.045 1***
β0.570 5***
表7  EGARCH模型估计结果
EGARCH模型系数结果
条件均值方程C-0.579 3***
C10.027 5***
条件方差方程ω0.273 6***
α1-0.037 0**
η10.678 0***
β1.103 9***
表8  EGARCH模型估计结果
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