非线性GARCH模型在中国股市波动预测中的应用研究

被引：46

作者：

刘国旗

机构：

来源：

统计研究 | 2000年 / 01期

关键词：

中国股票市场; 波动预测; 非线性GARCH模型;

D O I：

10.19343/j.cnki.11-1302/c.2000.01.010

中图分类号：

F224.0 [数量经济学];

学科分类号：

020209 ;

摘要：

ThispaperstudiestheperformanceoftheGARCHmodelandtwoofitsnon linear modificationstoforecastChina’sweeklystockmarketvolatility .Themodelsarethe QuadraticGARCHandtheGlosten ,JagannathanandRunklemodelswhichhavepro posedtodescribetheoftenobservednegativeskewnessinstockmarketindices.Wefind thattheQGARCHmodelisbestwhentheestimationsampledoesnotcontainextreme observationssuchasthestockmarketcrashandthattheGJRmodelcannotberecom mendedforforecasting .

引用

页码：49 / 52

页数：4

共 9 条

[1]

Alternative models for conditional stock market volatility. Pagan A R,Schwert G W. Journal of Econometrics . 1990

[2]

Conditional heteroskedasticity in asset returns: a new approach. Nelson D. Econometrica . 1990

[3]

Generalized autogressive conditional heteroskedasticity. Bollerslev T. Journal of Econometrics . 1986

[4]

Forecasting stock market prices:Lessons for forecasters. Granger C W J. International Journal of Forecasting . 1992

[5]

Quadratic ARCH models. Sentana E. The Review of Economic Studies . 1995

[6]

Stock market volatility and the information content of stock index options. Day T,Lewis C. Journal of Econometrics . 1992

[7]

Autogressive conditional heteroskedasticity with estimates of the variance of UK inflation. Engle R F. Econometrica . 1982

[8]

On the relation between the expected value and the volatility of nominal excess return on stocks. Glosten L,Jagannathan R,Runkle D. The Journal of Finance . 1992

[9]

ARCH modelling in finance: a review of the theory and empirical evidence. Bollerslev T,Chou R,Kroner K. Journal of Econometrics . 1992

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