均值溢出效应显著背景下A股市场杠杆效应研究——基于EGARCH模型
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摘要
目的在考虑了港股对A股的均值溢出效应后,对A股市场杠杆效应进行研究。方法利用EGARCH模型对以沪深300指数为代表的A股市场杠杆效应进行研究。结果一是A股市场波动存在明显的异方差性和信息冲击的非对称性;二是将均值溢出效应纳入分析框架建立的EGARCH模型在各项指标上的表现均普遍优于不考虑均值溢出效应而建立的EGARCH模型。结论就A股市场而言,负项干扰引起条件方差的变化比正项干扰大,即利空信息对波动的影响更大。
Objective Considering the mean spilover effect of HONG KONG stocks on A shares,this thesis focused on the leverage effect of A share market.Methods Using EGARCH model to research the leverage effect of A share market which is represented by CSI 300 index.Results This thesis suggests that the heteroskedasticity and asymmetry of the information are distinct.Meanwhile,the analysis indexes of the EGARCH model framework which has taken mean spilover effect into account are generally superior to the nomal EGARCH model.Conclusion The empirical research suggests that compared with positive interference,the variation of conditional variance is more sensitive to negative interference.That means the bad information has a greater effect on the volatility of A share market.
Objective Considering the mean spilover effect of HONG KONG stocks on A shares,this thesis focused on the leverage effect of A share market.Methods Using EGARCH model to research the leverage effect of A share market which is represented by CSI 300 index.Results This thesis suggests that the heteroskedasticity and asymmetry of the information are distinct.Meanwhile,the analysis indexes of the EGARCH model framework which has taken mean spilover effect into account are generally superior to the nomal EGARCH model.Conclusion The empirical research suggests that compared with positive interference,the variation of conditional variance is more sensitive to negative interference.That means the bad information has a greater effect on the volatility of A share market.
引文
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[5]李晓阳,黄毅祥.基于EGARCH(1,1)-M模型的国际石油价格与中国股指收益率的关联实证[J].西南大学学报(自然科学版),2013,35(10):15-23.
[6]朱信凯.信息与农产品价格波动:基于EGARCH模型的分析[J].管理世界,2012(11):57-66.
[7]张波,刘晓倩.基于EGARCH-M模型的沪深300股指期货跨期套利研究:一种修正的协整关系[J].统计与信息论坛,2017,32(04):34-40.
[8]KOOPMAN S J,HOL U E.The stochastic volatility in mean model:empirical evidence from international stock markets[J].Journal of Applied Econometrics,2002,17(06):667-689.
[9]AKGIRAY V.Conditional heteroskedasticity in time series of stock return:evidence and forecasts[J].Journal of Business,1989(62):55-80.
[2]NELSON D B.Conditional heteroskedasticity in asset returns:a new approach[J].Econometrica,1991(03):347-370.
[3]胡秋灵,马丽.我国股票市场和债券市场波动溢出效应分析[J].金融研究,2011(10):198-206.
[4]张宗成,王郧.股指期货波动溢出效应的实证研究:来自双变量EC-EGARCH模型的证据[J].华中科技大学学报(社会科学版),2009,23(04):75-80.
[5]李晓阳,黄毅祥.基于EGARCH(1,1)-M模型的国际石油价格与中国股指收益率的关联实证[J].西南大学学报(自然科学版),2013,35(10):15-23.
[6]朱信凯.信息与农产品价格波动:基于EGARCH模型的分析[J].管理世界,2012(11):57-66.
[7]张波,刘晓倩.基于EGARCH-M模型的沪深300股指期货跨期套利研究:一种修正的协整关系[J].统计与信息论坛,2017,32(04):34-40.
[8]KOOPMAN S J,HOL U E.The stochastic volatility in mean model:empirical evidence from international stock markets[J].Journal of Applied Econometrics,2002,17(06):667-689.
[9]AKGIRAY V.Conditional heteroskedasticity in time series of stock return:evidence and forecasts[J].Journal of Business,1989(62):55-80.