江汉学术 ›› 2016, Vol. 35 ›› Issue (4): 19-29.doi: 10.16388/j.cnki.cn42-1843/c.2016.04.003

• 社会学 经济 • 上一篇    下一篇

沪深股市波动性与“杠杆效应”问题再研究——基于非线性视域的GARCH族模型分阶段检验

潘锡泉   

  1. 浙江金融职业学院金融系,杭州 310018
  • 收稿日期:2016-04-19 修回日期:2016-04-19 出版日期:2016-08-15 发布日期:2016-07-11
  • 作者简介:潘锡泉,男,浙江新昌人,浙江金融职业学院金融系小微金融研究院助理研究员。
  • 基金资助:
    浙江省哲学社会科学规划课题“我国货币政策的资产价格效应问题研究”(13NDJC30YBM);浙江省金融教育基金会重点课题“杭州发展互联网金融的思考与建议”(2014Z12)

Re-research on the Chinese Stock Market’s Volatility and“Leverage Effect”——From the Perspective of Nonlinear Stage Test with GARCH Models

PAN Xiquan   

  1. Department of Finance,Zhejiang Vocational College of Finance,Hangzhou 310018
  • Received:2016-04-19 Revised:2016-04-19 Online:2016-08-15 Published:2016-07-11

摘要: 在非线性视域下Bai-Perron 多重结构突变检验的基础上,可采用GARCH 族模型对我国沪深股市的波动性和“杠杆效应”问题进行重新研究①。研究认为,第一,沪深股市在样本期内分别发生了2 次和1 次结构突变,沪市突变时点为2005 年2 月1 日和2007 年10 月16 日,深市突变时点为2007 年10 月31 日;第二,无论沪市还是深市,就其自身而言,波动性和“杠杆效应”在结构突变前后均表现出巨大的差异性,但比较沪深两市的总体特征却发现具有一定的趋同现象,尤其是在2007 年10 月结构突变之后的最近一段样本期内,两市的风险溢价行为均不存在,但却存在显著的非对称“杠杆效应”,表现为利空消息比利好消息会给投资者带来更大的冲击;第三,对具有趋同效应的共同样本期进行联动效应研究,可以发现沪深股市股价指数之间存在显著的联动效应,而收益率序列之间却不存在联动效应。

关键词: 沪深股市, 波动性, 结构突变, 杠杆效应, 非线性, GARCH 模型

Abstract: On the basis of Bai-Perron multiple structural mutation test from the nonlinear perspective,this thesis used GARCH models to re-research on the volatility and“leverage effect”of the Chinese stock market.The research finds:(1)in the sample period,structural mutation took place twice and once on the Shanghai and Shenzhen stock markets respectively:Feb. 1,2005 and Oct. 16,2007 in Shanghai and Oct. 31,2007 in Shenzhen;(2) the volatility and“leverage effect”before and after the structural mutation varied greatly either in the Shanghai Stock Exchange or Shenzhen,but the general characteristics of the Shanghai and Shenzhen markets had some similarities,especially in the last sample period after structural mutation in October 2007:both markets had no risk premiums but there was a significant asymmetrical“leverage effect” and bad news would give investors a greater impact than good news;(3)further research of the same sample period found,there was a significant coupling effect between Shanghai and Shenzhen’s stock price indexes but not between their yield sequences.

Key words: Shanghai and Shenzhen stock markets, volatility, structural mutation, leverage effect, nonlinear, GARCH models

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